\r\n\tBoth diagnosis and clinical manipulation of the patient with vasospasm is a unique and challenging situation. Multi-clinical approach is extremely mandatory. The patient must be treated in a center, which requires a experienced team with both neurological surgeons, interventional radiologists, neurologists and neuroanesthesiologists. Moreover, a well-equiped, isolated neurointensive care is needed for all patients suffering form subarachnoid hemorraghe. \r\n\tIn their daily practice, both neurological surgeons, interventional radiologists, neurologists, neuroanesthesiologists, and even intensive care providers have to deal and challenge of vasospasm. Numerous studies relevant to pathophysiological mechanisms underlying vasospasm had been published, but we still know little about the exact mechanisms causing vasospasm. In the last decades of modern medical era, despite the technological developments concerning the neurological care of the patients with vasospasm, we still have no effective treatment and preventive care of this devastating entity. \r\n\tThe aim of this book project is to provide in detailed knowledge to both physicians and scientists dealing with cerebral vasospasm. This book will attract interest of both students, residents, specialists and academics of neurological sciences.
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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"44903",title:"Cytomegalovirus Infection in Liver Transplantation",doi:"10.5772/56128",slug:"cytomegalovirus-infection-in-liver-transplantation",body:'
1. Introduction
With the global evolution of organ transplantation in humans a new class of patients with special problems related to opportunistic infections after transplantation has appeared [1, 2 ].Some of these challenges infections with members of the herpesvirus family. Among these viruses, human cytomegalovirus (HCMV) often affects immunocompromised patients, HCMV can be reactivated by immunosuppression and cause significant morbidity and mortality [3,4]. In the postoperative period, HCMV infection can result in serious complications in patients who received grafts by modulating the immune response [5]. However in immunocompetent individuals cytomegalovirus infection can be asymptomatic or cause symptoms similar to infectious mononucleosis syndrome, such as lymphadenopathy, fever, rash, malaise, arthralgia, hepatomegaly and splenomegaly [6].
This chapter presents the main clinical and epidemiological aspects related to cytomegalovirus infection and the importance of detection in liver transplant recipients.
2. Cytomegalovirus history
The discovery of HCMV began in 1881 when the histological effects of infection were observed in the kidney of a newborn child. In 1904, Ribbert identified the causative agent of "cytomegalic inclusion disease", whose name derives from the characteristic cytopathic effect, represented by increases in cell volume and intracellular cytoplasmic inclusions in infected tissues [7]. In 1881 and 1921 similar cell characteristics were reported by Goodpasture and Talbot in a fatal case associated with this virus involving lung, liver and kidney from a newborn child [8].
The first experimental evidence of the likely etiologic agent of "cytomegalic inclusion disease" was proposed by Cole and Kuttner in 1926, when they demonstrated the transmission of the disease in guinea pigs and suggested that this agent possessed characteristics of viral infection and was species-specific. Wolbach and Farber (1932) demonstrated the first evidence that the salivary gland virus was commonly involved and showed typical cytomegalic cells were found in 12% of children. In 1954, using the salivary infection mouse model, Smith isolated the virus in tissue culture [9].
In 1970 study groups were organized to evaluate the impact of infection in immunocompromised people and through this to propose infection control strategies. In the 1980s the control measures of CMV began with antiviral agents and immunological interventions [10].
3. Structure features and replication engine
CMV has an ultrastructure similar to other herpesviruses with four structural elements: an electron-dense core, an icosahedral symmetry capsid, a tegument occupying space between the capsid and an envelope steeped in glycoproteins and membrane proteins [11].
CMV carries a double-stranded DNA containing approximately 240 kb linear bases [12] encoding 33 structural proteins and an indefinite number of non-structural proteins, some of which are antigenic. The genome can be divided into two segments, designated as long component (L) and short (S) defined by repetitive sequence terminals (RT). The CMV has a complex genome due to the acquisitions of host genes and the duplication of viral genes [13]. It is a very thermolabile virus and its average life at 37 ° C is only 45 minutes, totally inactivated at 56 º C for 30 minutes [14].
During natural infection, viral replication can occur in epithelial, endothelial and muscle mesenchymal cells, hepatocytes, granulocytes and macrophages [15, 16]. In vivo studies with cells from immunocompetent and immunosuppressed patients show that CMV can commonly be isolated from polymorphonuclear leukocytes [17], which may represent an important replication site [14,16]. Variants of CMV are found in mice, monkeys and guinea pigs, but these strains are species-specific and do not infect humans [14].
The CMV replication mechanism occurs in three distinct stages, similar to other herpesviruses. The early phase occurs when the virus adheres to the host cell membrane (with the envelope loss and penetration into the cell), in the intermediate phase the gene expression and genome replication occur, and in the late phase, there is the assembly and release of new viral particles [16-18].
The “early” phase begins when surface proteins of the virion adhere to specific protein receptors on the cell surface through non-covalent bonds. The viral particles penetrate by endocytosis, entering pinocytic vesicles in which the envelope loss process is started, favored by a low pH. The rupture of the vesicles or fusion of the virus with the outer layer of the vesicle membrane deposits the core of the virus in the cell cytoplasm [13].
The intermediate phase lasts 24 hours, characterized by transcription and replication of viral DNA. The first step of viral gene expression is the synthesis of mRNA via host RNA polymerase inside the core. The mRNA is translated by the host ribosomes into early and late viral proteins. The early proteins are enzymes required for viral genome replication [19]. The late proteins include a polymerase replicating the viral genome [13].
In the late phase, viral particles newly formed are grouped together within the capsid and begin the process of budding, during which the nucleocapsid adheres to specific sites of the membrane and interacts with the protein matrix. At this point, a process of evagination occurs and an enveloped particle flows from the membrane surface [13].
4. Transmission and epidemiology
Infection is defined as seroconversion (an increase of 4 times or more in HCMV antibody titer in seronegative or seropositive patients), virus circulation in any body fluid such as urine, nasopharyngeal secretions or blood [7]. CMV infects only the human population and its transmission occurs both horizontally and vertically and may include oropharyngeal secretions, vaginal tears, seminal fluid, breast milk, urine, feces and blood [19]. In adulthood the CMV transmission may occur through heterosexual and homosexual contact, through blood and blood products and through organ transplantation, the latter being an important route of transmission [12,19, 20].
About 80% of the population between late childhood and early adolescence is already infected with CMV [21, 22] and can harbor the virus in various body sites, especially in the salivary glands and different types of leukocytes. With age the increased prevalence of antibodies is common. This may not depend on the geographical area, but the socio-economic status may be important [10, 23- 28]. The seroprevalence of CMV in populations at high socioeconomic level varies from 40% to 60%, increases after infection of early childhood and approximately 10% to 20% of children have their first infection episode before puberty [10]. In lower socioeconomic populations the seroprevalence level is higher, ranging from 80% to 100%. In Brazil, seroprevalence of cytomegalovirus averages 90% in adult populations [28].
5. Clinical manifestations
The clinical course of CMV in immunocompetent individuals may be asymptomatic or may resemble "Mononucleosis Syndrome" presented by persistent fever, myalgia, pharyngitis, lymphadenopathy, sweating and hepatosplenomegaly [10,28-34].
After primary infection, CMV persists in host tissues and may be reactivated to cause disease – usually in children with congenital infection, organ transplant recipients, cancer patients undergoing chemotherapy and patients with HIV disease [7,10,29,35].
Among the complications caused by CMV in transplanted patients increased long-term mortality and worsening graft survival are common [35-37]. Clinical disease caused by CMV is expressed by fever, malaise, myalgia, leukopenia (WBC less than 4.0000/mm3), increased transaminases (hepatitis), pulmonary (pneumonitis) and/or gastrointestinal (colitis, gastritis, esophagitis) and fever being the most common manifestation, which can also occur with neurological symptomatology compatible with encephalitis but these are rarer [29,38,39].
Clinical disease may reflect
Primary infection, when it occurs in patients previously seronegative;
Secondary infection occurs when the reactivation of latent infection or superinfection;
Tertiary infection by reinfection by other strains of the virus [7].
The source of infection for both primary infection and superinfection is may include graft and blood transfusions. Immunosuppression may cause reactivation of CMV [40]. About two thirds of patients with primary infection are symptomatic, less than 20% in viral reactivation have symptoms and about 40% of reinfected individuals have symptoms attributable to CMV [10]. When primary infection occurs after transplantation the clinical impact is significant [41]. This is most common following allocation of grafts from donors with positive serology to seronegative recipients [42]. Immunosuppressive drugs such as azathioprine and cyclosporine have been implicated in the facilitation of CMV disease [7].
Diagnostic criteria include clinical signs known to be caused by this virus [43,44]. In liver transplant patients with active CMV infection, about 80% will develop clinical manifestations of the disease and the rate may be higher when the recipient is seronegative and a donor is seropositive [44]. CMV infection is an independent risk factor for the development with opportunistic infections, as well as graft rejection [7]. The evidence of viral replication and clinical symptoms in transplant occurs mainly during the 1st to 4th month post-transplant.
The most common clinical manifestations are interstitial pneumonia, esophagitis, gastritis, colitis, retinitis, fever and delayed engraftment in bone marrow transplants [29,45]. During liver transplantation, primary infection tends to be more important as the CMV viremia may be limited to when virus replication is detected in peripheral blood or significant increase of specific antibodies without symptoms or viral syndrome presenting fever equal or greater than 38ºC, malaise, leukopenia, atypical lymphocytosis equal or less than 3-5% and thrombocytopenia [14, 37, 42, 45,46].
Antiviral treatment controls the acute manifestation of the disease in most cases, but may not eradicate the CMV with recurrence reported in 26-31% of solid organ transplant recipients.. [14, 36].
6. Diagnosis
The diagnosis of CMV infection can be done by serology, polymerase chain reaction (PCR), culture and viral antigenemia research. Early diagnosis is important as early treatment of asymptomatic active infection reduces morbidity [24, 31, 46, 47]. The first method of diagnosis used to identify the CMV was exfoliative cytology. This technique revealed the presence of large cells which had inclusions within the core, identified as cytomegalic inclusion. Later methods are more sensitive and specific. These are grouped into seven categories: cytological, histological, virus isolation, serological identification,, Immunofluorescence, detection of viral antigens and molecular methods [49, 48]…
Cytopathological techniques: These methods can be performed on tissue and secretions aspirated material [7,8], but have low sensitivity so they currently have little use in clinical practice.
Histological Techniques: A method of detecting inclusions by visualization of typical tissue. The finding of cells with typical inclusions allows often to correlate CMV lesion or dysfunction of the organ studied. Although this method has low sensitivity, it reveals invasive tissue disease [7]. The advantages are low cost, simplicity of use and availability of equipment.
Viral Isolation: CMV can be isolated from various biological materials, such as biological fluids (urine, saliva, blood, cervical secretions, breast milk, tears, semen, feces and washed aspirates organs) and tissue obtained from biopsies or autopsies [49, 50].
Serological methods: The modern serological methods detect the presence of IgM and IgG [51] usually by ELISA. This technique does not detect the virus in early stages of infection, as antibodies are produced by the host only after this phase.
Immunofluorescence (IF): A method that allows an early detection of the virus is immunofluorescence usually using commercially available antibodies.
Detection of Viral Antigens (antigenemia): Antigenemia offers high sensitivity and specificity. It is fast, direct and sensitive, and is considered a quantitative technique for viral load [54,55]. CMV antigenemia is one of the earlier tests with positive results [17, 25, 51- 58] and becomes positive on average 9-18 days before establishment of the disease. It has been widely used for the early detection of active infection in organ transplant recipients [17, 24, 25, 36, 56].
The additional advantage of this method is that results can be expressed quantitatively, allowing observation of the clinical response to treatment [17, 59]. The disadvantage of this technique is the speed needed to process the collected material without loss of sensitivity - 6 to 8 hours [17]. In patients with neutropenia, this test cannot be performed due to low granulocyte count. On this situation, molecular assays are used.
Molecular methods
Polymerase chain reaction-PCR: The qualitative PCR is often the first test to detect asymptomatic subclinical infection, but specific predictive value is low for the diagnosis of HCMV disease. It is not suitable for routine monitoring of patients on treatment [57]…why not???. It is a quick (4-6 hours), specific and extremely sensitive test but false positives may result from contamination during the test run. False negative results can also occur due to presence of inhibitors in the sample [55,60]. The sample type and method of extracting DNA from these samples must be carefully chosen to avoid this [31,61].
Nested PCR (Polymerase Chain Double): Nested PCR (N-PCR) has been used to increase the sensitivity and specificity of simple PCR. Here the product of the first PCR, amplified with a primer pair, is subjected to a new amplification reaction using another pair of primers internal to the first, the product being then detected by agarose gel electrophoresis [62]. Nested PCR technique to diagnose CMV infection produces results consistent with classical culture, reaching 100% specificity and 93% sensitivity in a shorter time frame [63- 66].
Real-time PCR: Real Time PCR amplification (RT PCR) presents high sensitivity and precision. It has been used for the detection and monitoring of viral load. Its sensitivity and specificity are directly related to the choice of "primers" and probes, and the accuracy is determined by the threshold cycle, which is calculated during the exponential phase of the reaction. Formation of a fluorescently labeled product is monitored at each amplification cycle in a single instrument generating quantitative results. [58].
7. Treatment
Ganciclovir has been the “gold standard” for treatment of CMV disease although resistance to this drug has been reported and should be considered in unresponsive patients. Some studies have focused on genotyping of CMV that could indicate samples that were resistant to conventional treatment. Inadequate dosing may reduce clinical efficacy and promote resistance (44)
Antiviral administration is generally initiated in the immediate or early post-transplant period, and continues for 3 to 6 months. Various antiviral drugs have been used, including acyclovir, valaciclovir, intravenous ganciclovir, oral valganciclovir or intravenous (IV) ganciclovir, and valganciclovir. In preventive therapy, laboratory monitoring detects asymptomatic viral replication and antiviral therapy is initiated to prevent progression to clinical disease. For non severe CMV disease, oral valganciclovir (900 mg orally every 12 hr) or IV ganciclovir (5 mg/kg every 12hr) are recommended as first-line treatment. Renal function should be monitored frequently during treatment, with estimated or measured glomerular filtration rate. Optimal length of treatment should be achieved by monitoring weekly viral loads and treating until one or two consecutive negative samples are obtained, but not shorter than 2 weeks. Duration should reflect the likelihood of recurrent CMV infection. In cases of serious disease and in tissue-invasive disease without viremia, longer treatment periods with clinical monitoring of the specific disease manifestation are recommended. In cases of recurrent CMV disease, prophylaxis after retreatment may need to be prolonged. [44].
8. Transplantation
CMV seroprevalence is high in developing countries such as Brazil, so most of the patients and/or donors is CMV IgG positive. The techniques chosen for the laboratorial monitoring in our service after liver transplantation are antigenemia and Nested-PCR (N-PCR). These techniques detect the active viral replication and minimize the damage of the disease caused by CMV (see Section xy).
We diagnose active infection from one positive result by antigenemia, or two positive N-PCR findings over an interval equal or smaller than 30 days. As antigenemia can detect CMV a few days to one week before the appearance of the symptoms, the Ganciclovir is initiated after the detection of a positive cell even without clinical symptoms if the patient presents IgG negative and the donor presents IgG positive. Patients are monitored while in hospital and after discharge following a protocol: weekly from the first to the second month, fortnightly in the third-fourth months and monthly until six months. After this period the antigenemia or N-PCR is performed only if there is a suggestive clinical diagnosis of CMV infection. The assessment of antigenemia also provides an estimate of viral load that is useful in the differentiation of CMV disease from other complications. Thus we evaluate the efficacy of antiviral therapy and have capacity to detect drug resistance.
CMV is frequently detected in our patients after liver transplantation [24,25,30,31]. Detection of N-PCR and antigenemia are useful markers for active infection [30,31].The rates of CMV found in our groups are similar to other services [24,25,30-32].
We also observed that symptomatic CMV infection occurs during the first three months after transplantation. We consider that this high incidence of symptomatic CMV infection is due to the high prevalence of the virus in Brazilian population. The mean time for initial detection CMV is around 29 days following transplantation (range: 0-99 days) [30]..
In our service, CMV DNA diagnosed in pretransplantation graft biopsy specimens remained positive posttransplantation on graft biopsies. This common complication negatively influences liver transplantation outcomes and is a risk factor to develop acute cellular rejection episodes [67].Ganciclovir prophylaxis for CMV is not performed at our institution unless the patient is preoperative negative IgG and the donor is CMV positive. Prophylaxis is performed only for herpes simplex type 1 with Acyclovir.
Another relevant issue at our service is opportunistic infections, which are often seen in patients at risk for CMV and have been recognized by our staff as a significant risk factor for graft failure and death [24]. Active CMV infection may increase the risk of bacterial, fungal, viral, and others, as well as post-transplant lymphoproliferative disease. [31] This includes co-infections by other viruses of the same family (HHV-6, HHV-7) [24,32].
The clinical impact of CMV-infected patients observed by our team [24] shows that it is extremely important to follow up these patients. These data have helped the medical staff making therapeutic strategies to minimize risks caused by this betaherpesvirus.
Figure 1.
Nuclei of neutrophils stained in brown indicating positive pp65-atigenemia (counterstained with Harris’s hematoxylin). Mouse C10 and C11 monoclonal antibodies against pp65-matrix CMV antigen and rabbit anti-mouse Ig horseradish peroxidase conjugate. The reaction was revealed by hydrogen peroxide and amino-ethyl-carbazole24
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t\t
Virus
\n\t\t\t
Synonym
\n\t\t\t
Subfamily
\n\t\t\t
Abbreviation
\n\t\t
\n\t\t
\n\t\t\t
Human Herpesvirus-1
\n\t\t\t
Herpes simplex-1
\n\t\t\t
||
\n\t\t\t
HSV-1/HHV-1
\n\t\t
\n\t\t
\n\t\t\t
Human Herpesvirus -2
\n\t\t\t
Herpes simplex-2
\n\t\t\t
||
\n\t\t\t
HSV-2/HHV-2
\n\t\t
\n\t\t
\n\t\t\t
Human Herpesvirus -3
\n\t\t\t
Varicella-zoster
\n\t\t\t
||
\n\t\t\t
VZV/HHV-3
\n\t\t
\n\t\t
\n\t\t\t
Human Herpesvirus -4
\n\t\t\t
Epstein-Barr
\n\t\t\t
||
\n\t\t\t
EBV/HSV-4
\n\t\t
\n\t\t
\n\t\t\t
Human Herpesvirus -5
\n\t\t\t
Cytomegalovirus
\n\t\t\t
||
\n\t\t\t
HCMV/CMV/HHV-5
\n\t\t
\n\t\t
\n\t\t\t
Human Herpesvirus -6
\n\t\t\t
None
\n\t\t\t
||
\n\t\t\t
HHV-6
\n\t\t
\n\t\t
\n\t\t\t
Human Herpesvirus -7
\n\t\t\t
None
\n\t\t\t
||
\n\t\t\t
HHV-7
\n\t\t
\n\t\t
\n\t\t\t
Human Herpesvirus -8
\n\t\t\t
None
\n\t\t\t
||
\n\t\t\t
KSHV/HHV-8
\n\t\t
\n\t
Table 1.
Complete list of human herpesvirus
9. Conclusion
Few patients remain free of betaherpesvirus after liver transplantation. Active CMV infection is common especially in the first weeks after grafting. We believe it is important to continue monitoring CMV infection after transplantation, especially when the prevalence in the general population is high.
Acknowledgments
Biologist Eliana Duarte Quizini Bueno
This study received financial support from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES).
\n',keywords:null,chapterPDFUrl:"https://cdn.intechopen.com/pdfs/44903.pdf",chapterXML:"https://mts.intechopen.com/source/xml/44903.xml",downloadPdfUrl:"/chapter/pdf-download/44903",previewPdfUrl:"/chapter/pdf-preview/44903",totalDownloads:1303,totalViews:308,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,dateSubmitted:"July 18th 2012",dateReviewed:"February 13th 2013",datePrePublished:null,datePublished:"May 29th 2013",dateFinished:null,readingETA:"0",abstract:null,reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/44903",risUrl:"/chapter/ris/44903",book:{slug:"manifestations-of-cytomegalovirus-infection"},signatures:"Ana Maria Sampaio, Ana Carolina Guardia, Arlete Milan, Elaine\nCristina Ataíde, Rachel Silveira Bello Stucchi, Sandra Botelho Cecilia\nCosta and Ilka de Fatima Santana Ferreira Boin",authors:[{id:"78626",title:"Prof.",name:"Ilka",middleName:null,surname:"Boin",fullName:"Ilka Boin",slug:"ilka-boin",email:"ilkaboin@gmail.com",position:null,institution:{name:"State University of Campinas",institutionURL:null,country:{name:"Brazil"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Cytomegalovirus history",level:"1"},{id:"sec_3",title:"3. Structure features and replication engine",level:"1"},{id:"sec_4",title:"4. Transmission and epidemiology",level:"1"},{id:"sec_5",title:"5. Clinical manifestations",level:"1"},{id:"sec_6",title:"6. Diagnosis ",level:"1"},{id:"sec_7",title:"7. Treatment",level:"1"},{id:"sec_8",title:"8. Transplantation",level:"1"},{id:"sec_9",title:"9. Conclusion",level:"1"},{id:"sec_10",title:"Acknowledgments",level:"1"},{id:"sec_10",title:"Acknowledgments",level:"2"}],chapterReferences:[{id:"B1",body:'LevinsonWJawetzEMedical microbiology & immunology: examination and board review 6th ed. New York: Lange Medical Books/McGraw-Hill 2000206282Part. IV.'},{id:"B2",body:'Tong CYWBakran A, Willians H, Cheung CY, Peiris JSM. Association of human herpes virus 7 with CMV disease in renal transplant recipients. Transplantation 200070213'},{id:"B3",body:'GuoZChenH. RLiuX. DBianJ. MHeX. FLouJ. Xet alClinical analysis of cytomegalovirus infection after allogeneic hematopoietic stem cell transplantation Zhong Shi Yan Xue Ye Xue Za Zhi 20122049714'},{id:"B4",body:'LautenschlagerIHalmeLHockerstedtKKrogerusLTaskinenECytomegalovirus infection of the Liver Transplant: Virological, Histological, Immunological, and Clinical Observations. Transpl Infect Dis 2006821'},{id:"B5",body:'WeigandKSchnitzlerPSchimidtJChahoudFGotthardtDSchemmerPet alCytomegalovirus Infection After Liver Transplantation Incidence, Risks, And Benefits of Prophylaxis. Transplant Proc 2010422634'},{id:"B6",body:'SchroederRMichelonTFagundesIBortolottoALammerhirtEOliveiraJet alCytomegalovirus disease latent and active infection rates during the first trimester after kidney transplantation. Transplant Proc 2004368968'},{id:"B7",body:'Maya TC; Azulay DRInfecção pelo Citomegalovirus. In: Lupi O; Silva AS; Pereira Jr. Herpes- Cliníca, Diagnóstico e Tratamento, 1° Ed., Medsi Editora Médica e Científica 20008135'},{id:"B8",body:'DrewW. LDiagnosis of cytomegalovirus infection. Rev Infect Dis 19883468'},{id:"B9",body:'SmithI. LCherringtonJ. MJilesR. EFullerM. DFreemanW. RSpectorS. AHigh-level resistance of cytomegalovirus to ganciclovir is associated with alterations in both the UL97 and DNA polymerase genes. J Infect Dis 199717616977'},{id:"B10",body:'Costa SCBInfecção por citomegalovirus (CMV); epidemiologia, diagnóstico e tratamento. Rev Bras Clín Ter 19991828\n\t\t\t'},{id:"B11",body:'BraunD. LDominguezGPelletP. EHuman Herpesvirus 6. Clinic Microbiol Review 199710521\n\t\t\t'},{id:"B12",body:'BrennanD. CCytomegalovirus in Renal Transplantation. J Am Soc Nephrology 200112848'},{id:"B13",body:'LevinsonWJawetzEMedical Microbiology & Immunology: Examination & Board Review 6th ed. New York: Lange Medical Books/McGraw-Hill 2000206282\n\t\t\t'},{id:"B14",body:'RowshaniA. TClinical and immunologic aspects of cytomegalovirus infection in solid organ transplant recipients. Transplantation 200579381386'},{id:"B15",body:'SmithV. VWilliamsA. JNovelliVMaloneMExtensive enteric leiomyolysis due to cytomegalovirus enterocolitis in vertically acquired human immunodeficiency virus infection in infants. Pediatr Dev Pathol 2000365916\n\t\t\t'},{id:"B16",body:'GernaGPercivalleEBaldantiFSozzaniSLanzariniPGeninIet alHuman cytomegalovirus replicates abortively in polymorphonuclear leukocytes after transfer from infected endothelial cells via transient microfusion events. J Virol 20007456295638\n\t\t\t'},{id:"B17",body:'Bonon SHAMenoni SMF, Rossi CL, Souza CA, Costa SCB. Surveillance of cytomegalovirus infection in hematopoietic stem cell transplantation patients. J Infection 20055013013'},{id:"B18",body:'Santos RLBPropriedades Gerais dos Herpesvírus. In: Lupi A, Silva AS, Pereira JR, AC.- Herpes Clín Diag Trat 1ª edição, Medsi Editora Médica e Científica Ltda 20001079'},{id:"B19",body:'BresnahanW. AShenkTA Subset of viral transcripts package within human cytomegalovirus particles. Science\n\t\t\t\t\t2000'},{id:"B20",body:'DragoFAragoneM. GLuagniCReboraACytomegalovirus Infection in normal and immunocompromised humans. Dermatology 2000200189'},{id:"B21",body:'AlmeidaLN BAzevedoR SAmakuMMassadE. Cytomegalovirus seroepidemiology in an urban community of são paulo, Brazil. Rev Saúde Pública 2001352124129'},{id:"B22",body:'GupteatMDiaz-mitomaFFeberJShawLForgetCFillerGTissue HHV6 and HHV7 determination in pediatric solid organ recipients- a Pilot Study. Ped Transplant 20037458463'},{id:"B23",body:'PannutiC. SVilasBNeto LSVA, Ângelo MJO, Sabbada E. Detecção de anticorpos IgM nas interações primárias e secundárias pelo citomegalovirus em pacientes submetidos a transplante renal. Inst Med Trop 198729317322'},{id:"B24",body:'SampaioA. MThomasiniR. LGuardiaA. CStucchiR. SRossiC. LCostaS. Cet alCytomegalovirus, human herpesvirus-6, and human herpesvirus-7 in adult liver transplant recipients: diagnosis based on antigenemia. Transplant Proc 201143413579'},{id:"B25",body:'MilanASampaioA. MGuardiaA. CPavanC. RAndradeP. DBononS. Het alMonitoring and detection of cytomegalovirus in liver transplant recipients. Transplant Proc 20114313601'},{id:"B26",body:'MillerC. SAvdiushkoS. AKryscioR. JDanaherR. JJacobR. JEffect of prophylactic valaciclovir on the presence of human herpesvirus dna in saliva healthy individuals after dental treatment. J Clin Microbiol 20055217380'},{id:"B27",body:'CrumpackerC. SWadhwaSCytomegalovirus. In: Mandell GL, Bennett JE, Dolin R. Principles and Practice of Infectious Disease. 6 ed. Philadelphia: Elsevier Inc 2005178696'},{id:"B28",body:'AquinoV. HFigueiredoL. MCytomegalovirus Infection in renal transplant recipients diagnosed by Nested-PCR. Braz J Med 200134293101'},{id:"B29",body:'RazonableR. RPayaC. VInfections and allograft rejection- Intertwined complications of organ transplantation. Swiss Med Wkly 200513539'},{id:"B30",body:'CostaF. ASokiM. NAndradeP. DBonon SHA, Thomasini RL, Sampaio AM, et al. Simultaneous monitoring of cmv and human herpesvirus 6 infections and diseases in liver transplant patients: one-year follow-up. Clinics 20116694953'},{id:"B31",body:'ThomasiniR. LSampaioA. MBononS. HBoinI. FLeonardiL. SLeonardiMet alDetection and monitoring of human herpesvirus 7 in adult liver transplant patients: impact on clinical course and association with cytomegalovirus. Transplant Proc 20073915379'},{id:"B32",body:'GuardiaA. CStucchiR. SSampaioA. MMilanACostaS. CPavanC. Ret alhuman herpesvirus 6 in donor biopsies associated with the incidence of clinical cytomegalovirus disease and hepatitis c virus recurrence. Int J Infect Dis 2011161249\n\t\t\t'},{id:"B33",body:'SebekováKFeberJCarpenterBShawLKarnauchowTDiaz-mitomaFet alTissue viral dna is associated with chronic allograft nephropathy 200595598603'},{id:"B34",body:'PannutiC. SCitomegalia. In: Ferreira, A. W.; Ávila, S.L.M. eds. Diagnóstico Laboratorial das principais Doenças Infecciosas e Autoimunes, 2ª. Edição, Editora Guanabara Koogan 2001568'},{id:"B35",body:'LinharesLSanclementeGCerveraCHoyoICofánFRicartM. Jet alInfluence of cytomegalovirus disease in outcome of solid organ transplant patients. Transplant Proc 20114321452148\n\t\t\t'},{id:"B36",body:'SampathkumarPPayaC. VManagement of cytomegalovirus infection after liver transplantation. Liver Transpl 200062144156'},{id:"B37",body:'AngelisMCooperJFreemanR. BImpact of donor infections on outcome of orthotopic liver transplantation 2003451462'},{id:"B38",body:'LjungmanPGriffithsPPayaCDefinition of cytomegalovirus infection and disease in transplant recipients. Clin Infect Dis 2002'},{id:"B39",body:'HumarAKumarDGrayMMoussaGVenkataramanSKumarRTipplesG. AA Prospective assessment of cytomegalovirus immune evasion gene transcription profiles in transplant patients with cytomegalovirus infection. Transplantation 200783912006'},{id:"B40",body:'Van Der MeerJtm Drew.; Bowden RA.; Galasso Gl.; Griffiths PD.; Jabs DA; et al. Summary of the international consensus symposium on advances in the diagnosis, treatment and prophylaxis of cytomegalovirus infection. Antiviral Res 199632119140'},{id:"B41",body:'SinghNWannstedtCKeyesLWagenerM. MVeraMCacciarelliT. Vet alImpact of evolving trends in recipient and donor characteristics on cytomegalovirus infection in liver transplant recipients. Transplantation 20047710610'},{id:"B42",body:'FreemanR. BRisk factors for cytomegalovirus viremia and disease developing after prophylaxis in high-risk solid-organ transplant recipients. Transplantation 20047817651773\n\t\t\t'},{id:"B43",body:'MustafaM. MCytomegalovirus infection and disease in the immunocompromised host. The Ped Inf Dis J 199413249259'},{id:"B44",body:'KottonC. NHumarACaliendoA. MEmeryVLautenschlagerILazzarottoTet alTransplantation Society International CMV Consensus Group. International consensus guidelines on the management of cytomegalovirus in solid organ transplantation. Transplantation 20108977995'},{id:"B45",body:'SeehoferDet alCMV hepatitis after liver transplantation: incidence, clinical course, and long-term follow-up. Liver Transpl 2002\n\t\t\t'},{id:"B46",body:'HoppeLBressaneRLagoL. SSchiavoF. LMarK. LCastisani CPC. Risk factors associated with cytomegalovirus-positive antigenemia in orthotopic liver transplant patients. Transplant Proc 200436961963'},{id:"B47",body:'LautenschlagerJLappalainenMLinnavuoriKSuniJHockerstedtKCMV infection is usually associated with concurrent HHV-6 and HHV-7 antigenemia in liver transplant Patients. J Clin Virol 20022557'},{id:"B48",body:'ChouSNewer methods for diagnosis of cytomegalovirus infection. Rev Infect Dis 1990'},{id:"B49",body:'LautenschlagerILinnavuoriKLappalainenMSuniJHöckerstedtKHHV-6 reactivation is often associated with CMV infection in liver transplant patients. Transpl Int 2000131351'},{id:"B50",body:'HoMCytomegalovirus: Biology and infection. Plen Publis Corp 19911440\n\t\t\t'},{id:"B51",body:'BiganzoliPFerreyraLSiciliaPCarabajalCFrattariSLittvikAet alIgG Subclasses and DNA detection of HHV-6 and HHV-7 in healthy individuals. J Med Virol 201082167983'},{id:"B52",body:'RasmussenLKelsallDNelsonRCarneyWHirschMWinstonDet alVirus-specific IgG and IgM antibodies in normal and immunocompromised subjects infected with cytomegalovirus. J Infect Dis 198214521919'},{id:"B53",body:'ChantlynneL. GAblashiD. VSeroepidemiology of Kaposi’s sarcoma-associated herpesvirus (KSHV). Semin Cancer Biol 1999'},{id:"B54",body:'Van Den Berg APKlompmaker IJ, Haagsma EB, Scolten-Sampson A, Bijlevel CMA; Schirm J, et al. Antigenemia in the diagnosis and monitoring of active cytomegalovirus infection after liver transplantation. J Infect Dis 1991164265270\n\t\t\t'},{id:"B55",body:'TheT. HVan Der PloegMVan Der BergA. PVliegerA. Met alDirect detection of cytomegalovirus in peripheral blood leukocytes: a review of the antigenemia assay and polymerase chain reaction. Transplantation 199254193198'},{id:"B56",body:'SchroederRMichelonTFagundesIET alAntigenemia for Cytomegalovirus in renal transplantation: choosing a cutoff for the diagnosis criteria in cytomegalovirus disease. Transplant Proc 20053727812783'},{id:"B57",body:'AmorimM. LCabedaJ. MSecaRMendesA. CCastroA. PAmorimJ. MCMV infection of liver transplant recipients: comparison of antigenemia and molecular biology assays. BMC Infect Dis 2001'},{id:"B58",body:'BordilsAPlumedJ. SRamosDBeneytoIMascarósVMolinaJ. Met alcomparison of quantitative pcr and antigenemia in cytomegalovirus infection in renal transplant recipients. Transplant Proc 20053737569'},{id:"B59",body:'LianghuiGShusenZTinobaLYanSWellingWAnweiLDeferred versus prophylactic therapy with ganciclovir for cytomegalovirus in allograft liver transplantation. Transplant Proc 20043615021505'},{id:"B60",body:'PiiparinenHHöckerstedtKGrönhagen-riskaCLautenschlagerIComparison of two quantitative CMV PCR tests, Cobas Amplicor CMV monitor and taqman assay, and 65assay in the determination of viral loads from peripheral blood of organ transplant patients. J Clin Virol 2004\n\t\t\t'},{id:"B61",body:'PeigoM. FThomasiniR. LPugliaA. LCostaS. CBononS. HBoinI. Fet alHuman herpesvirus-7 in brazilian liver transplant recipients. a follow-op comparison between molecular and immunological assays. Transplant Infect Dis 200911497502\n\t\t\t'},{id:"B62",body:'AbecassisM. MKoffronA. JBuckinghamMKaufmanD. BFryerJ. PStuartJet alRole of PCR in the diagnosis and management of cmv in solid organ recipients. what is the predictive value for development of disease and should pcr be used to guide antiviral therapy. Transplant Proc 1997'},{id:"B63",body:'OliveD. Met alMufti S, Simsek M, Fayez H, al Nakib W. Direct Detection of Human Cytomegalovirus in Urine Specimens From Renal Transplant Patients Following Polymerase Chain Reaction Amplification. J Med Virol 19892942327'},{id:"B64",body:'CostaF. ASokiM. NAndradeP. DBonon SHA, Thomasini RL, Sampaio AM, et al. Simultaneous monitoring of CMV and human herpesvirus 6 infections and diseases in liver transplant patients: one-year follow-up. Clinics 20116694953\n\t\t\t'},{id:"B65",body:'EvansM. JEdwards-springYMyersJWendtAPovinelliDAmsterdamDet alPolymerase chain reaction assays for the detection of cytomegalovirus in organ and bone marrow transplant recipients. Immunol Invest 1997'},{id:"B66",body:'GernaGZavattoniMPercivalleEZellaDTorselliniMRevelloM. GDiagnosis of human cytomegalovirus infections in the immunocompromised host. Clin Diagn Virol 1996'},{id:"B67",body:'Guardia-silvaA. CStucchiR. SSampaioA. MMilanACostaS. CBoinI. FDetection of cytomegalovirus and human herpesvirus-6 DNA in liver biopsy specimens and their correlation with rejection after liver transplantation. Transplant Proc. 201244824414'}],footnotes:[],contributors:[{corresp:null,contributorFullName:"Ana Maria Sampaio",address:null,affiliation:'
Department of Surgery - Liver Transplant Unit of the State University of Campinas, Brazil
Department of Clinical Medicine - Liver Transplantation Unit, State University of Campinas, Brazil
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Department of Surgery - Liver Transplant Unit of the State University of Campinas, Brazil
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Bangs",slug:"michael-j.-bangs"},{id:"169010",title:"Dr.",name:"Wanapa",middleName:null,surname:"Ritthison",fullName:"Wanapa Ritthison",slug:"wanapa-ritthison"}]},{id:"43254",title:"Understanding Anopheles Diversity in Southeast Asia and Its Applications for Malaria Control",slug:"understanding-anopheles-diversity-in-southeast-asia-and-its-applications-for-malaria-control",signatures:"Katy Morgan, Pradya Somboon and Catherine Walton",authors:[{id:"154092",title:"Dr.",name:"Catherine",middleName:null,surname:"Walton",fullName:"Catherine Walton",slug:"catherine-walton"},{id:"154867",title:"Dr.",name:"Katy",middleName:null,surname:"Morgan",fullName:"Katy Morgan",slug:"katy-morgan"},{id:"169019",title:"Dr.",name:"Pradya",middleName:null,surname:"Somboon",fullName:"Pradya Somboon",slug:"pradya-somboon"}]},{id:"44155",title:"The Systematics and Bionomics of Malaria Vectors in the Southwest Pacific",slug:"the-systematics-and-bionomics-of-malaria-vectors-in-the-southwest-pacific",signatures:"Nigel W. Beebe, Tanya L. Russell, Thomas R. Burkot, Neil F. Lobo and\nRobert D. Cooper",authors:[{id:"152080",title:"Dr.",name:"Nigel",middleName:null,surname:"Beebe",fullName:"Nigel Beebe",slug:"nigel-beebe"},{id:"169012",title:"Dr.",name:"Tanya",middleName:null,surname:"L. Russell",fullName:"Tanya L. Russell",slug:"tanya-l.-russell"},{id:"169013",title:"Dr.",name:"Thomas",middleName:null,surname:"R. Burkot",fullName:"Thomas R. Burkot",slug:"thomas-r.-burkot"},{id:"169014",title:"Dr.",name:"Neil",middleName:null,surname:"F. Lobo",fullName:"Neil F. Lobo",slug:"neil-f.-lobo"},{id:"169015",title:"Dr.",name:"Robert",middleName:null,surname:"D. Cooper",fullName:"Robert D. Cooper",slug:"robert-d.-cooper"}]},{id:"43671",title:"Ecology of Larval Habitats",slug:"ecology-of-larval-habitats",signatures:"Eliška Rejmánková, John Grieco, Nicole Achee and Donald R.\nRoberts",authors:[{id:"151632",title:"Prof.",name:"Nicole",middleName:null,surname:"Achee",fullName:"Nicole Achee",slug:"nicole-achee"},{id:"152601",title:"Prof.",name:"Eliska",middleName:null,surname:"Rejmankova",fullName:"Eliska Rejmankova",slug:"eliska-rejmankova"},{id:"169016",title:"Dr.",name:"John",middleName:null,surname:"Grieco",fullName:"John Grieco",slug:"john-grieco"}]},{id:"43954",title:"From Anopheles to Spatial Surveillance: A Roadmap Through a Multidisciplinary Challenge",slug:"from-anopheles-to-spatial-surveillance-a-roadmap-through-a-multidisciplinary-challenge",signatures:"Valérie Obsomer, Nicolas Titeux, Christelle Vancustem, Grégory\nDuveiller, Jean-François Pekel, Steve Connor, Pietro Ceccato and\nMarc Coosemans",authors:[{id:"131417",title:"Dr.",name:"Valérie",middleName:null,surname:"Obsomer",fullName:"Valérie Obsomer",slug:"valerie-obsomer"},{id:"152754",title:"Prof.",name:"Marc",middleName:null,surname:"Coosemans",fullName:"Marc Coosemans",slug:"marc-coosemans"},{id:"153949",title:"Dr.",name:"Pietro",middleName:null,surname:"Ceccato",fullName:"Pietro Ceccato",slug:"pietro-ceccato"},{id:"153950",title:"Dr.",name:"Gregory",middleName:null,surname:"Duveiller",fullName:"Gregory Duveiller",slug:"gregory-duveiller"},{id:"153952",title:"Dr.",name:"Christelle",middleName:null,surname:"Vancutsem",fullName:"Christelle Vancutsem",slug:"christelle-vancutsem"},{id:"153980",title:"Dr.",name:"Nicolas",middleName:null,surname:"Titeux",fullName:"Nicolas Titeux",slug:"nicolas-titeux"},{id:"154158",title:"Dr.",name:"Steve J",middleName:null,surname:"Connor",fullName:"Steve J Connor",slug:"steve-j-connor"},{id:"167685",title:"MSc.",name:"Jean-Francois",middleName:null,surname:"Pekel",fullName:"Jean-Francois Pekel",slug:"jean-francois-pekel"}]},{id:"43960",title:"Simian Malaria Parasites: Special Emphasis on Plasmodium knowlesi and Their Anopheles Vectors in Southeast Asia",slug:"simian-malaria-parasites-special-emphasis-on-plasmodium-knowlesi-and-their-anopheles-vectors-in-sout",signatures:"Indra Vythilingam and Jeffery Hii",authors:[{id:"151116",title:"Dr.",name:"Indra",middleName:null,surname:"Vythilingam",fullName:"Indra Vythilingam",slug:"indra-vythilingam"},{id:"169006",title:"Dr.",name:"Jeffery",middleName:null,surname:"Hii",fullName:"Jeffery Hii",slug:"jeffery-hii"}]},{id:"44039",title:"Thermal Stress and Thermoregulation During Feeding in Mosquitoes",slug:"thermal-stress-and-thermoregulation-during-feeding-in-mosquitoes",signatures:"Chloé Lahondère and Claudio R. Lazzari",authors:[{id:"151619",title:"Prof.",name:"Claudio",middleName:null,surname:"R. Lazzari",fullName:"Claudio R. Lazzari",slug:"claudio-r.-lazzari"},{id:"151620",title:"Ms.",name:"Chloé",middleName:null,surname:"Lahondère",fullName:"Chloé Lahondère",slug:"chloe-lahondere"}]},{id:"43955",title:"The Anopheles Mosquito Microbiota and Their Impact on Pathogen Transmission",slug:"the-anopheles-mosquito-microbiota-and-their-impact-on-pathogen-transmission",signatures:"Mathilde Gendrin and George K. Christophides",authors:[{id:"154007",title:"Dr.",name:"Mathilde",middleName:null,surname:"Gendrin",fullName:"Mathilde Gendrin",slug:"mathilde-gendrin"},{id:"154008",title:"Prof.",name:"George",middleName:"K",surname:"Christophides",fullName:"George Christophides",slug:"george-christophides"}]},{id:"43829",title:"Bacterial Biodiversity in Midguts of Anopheles Mosquitoes, Malaria Vectors in Southeast Asia",slug:"bacterial-biodiversity-in-midguts-of-anopheles-mosquitoes-malaria-vectors-in-southeast-asia",signatures:"Sylvie Manguin, Chung Thuy Ngo, Krajana Tainchum, Waraporn\nJuntarajumnong, Theeraphap Chareonviriyaphap, Anne-Laure\nMichon and Estelle Jumas-Bilak",authors:[{id:"50017",title:"Prof.",name:"Sylvie",middleName:null,surname:"Manguin",fullName:"Sylvie Manguin",slug:"sylvie-manguin"},{id:"75315",title:"Prof.",name:"Theeraphap",middleName:null,surname:"Chareonviriyaphap",fullName:"Theeraphap Chareonviriyaphap",slug:"theeraphap-chareonviriyaphap"},{id:"88985",title:"Prof.",name:"Anne-Laure",middleName:null,surname:"Michon",fullName:"Anne-Laure Michon",slug:"anne-laure-michon"},{id:"88986",title:"Prof.",name:"Estelle",middleName:null,surname:"Jumas-Bilak",fullName:"Estelle Jumas-Bilak",slug:"estelle-jumas-bilak"},{id:"156016",title:"MSc.",name:"Chung Thuy",middleName:null,surname:"Ngo",fullName:"Chung Thuy Ngo",slug:"chung-thuy-ngo"},{id:"156018",title:"MSc.",name:"Krajana",middleName:null,surname:"Tainchum",fullName:"Krajana Tainchum",slug:"krajana-tainchum"},{id:"156019",title:"Dr.",name:"Waraporn",middleName:null,surname:"Juntarajumnong",fullName:"Waraporn Juntarajumnong",slug:"waraporn-juntarajumnong"}]},{id:"43899",title:"Distribution, Mechanisms, Impact and Management of Insecticide Resistance in Malaria Vectors: A Pragmatic Review",slug:"distribution-mechanisms-impact-and-management-of-insecticide-resistance-in-malaria-vectors-a-pragmat",signatures:"Vincent Corbel and Raphael N’Guessan",authors:[{id:"152666",title:"Dr.",name:"Vincent",middleName:null,surname:"Corbel",fullName:"Vincent Corbel",slug:"vincent-corbel"},{id:"169017",title:"Dr.",name:"Raphael",middleName:null,surname:"N'Guessan",fullName:"Raphael N'Guessan",slug:"raphael-n'guessan"}]},{id:"43851",title:"Perspectives on Barriers to Control of Anopheles Mosquitoes and Malaria",slug:"perspectives-on-barriers-to-control-of-anopheles-mosquitoes-and-malaria",signatures:"Donald R. Roberts, Richard Tren and Kimberly Hess",authors:[{id:"151439",title:"Prof.",name:"Donald",middleName:null,surname:"R. Roberts",fullName:"Donald R. Roberts",slug:"donald-r.-roberts"},{id:"151656",title:"Mr.",name:"Richard",middleName:null,surname:"Tren",fullName:"Richard Tren",slug:"richard-tren"},{id:"154152",title:"Ms.",name:"Kimberly",middleName:null,surname:"Hess",fullName:"Kimberly Hess",slug:"kimberly-hess"}]},{id:"43874",title:"Residual Transmission of Malaria: An Old Issue for New Approaches",slug:"residual-transmission-of-malaria-an-old-issue-for-new-approaches",signatures:"Lies Durnez and Marc Coosemans",authors:[{id:"152754",title:"Prof.",name:"Marc",middleName:null,surname:"Coosemans",fullName:"Marc Coosemans",slug:"marc-coosemans"},{id:"169018",title:"Dr.",name:"Lies",middleName:null,surname:"Durnez",fullName:"Lies Durnez",slug:"lies-durnez"}]},{id:"44330",title:"Vector Control: Some New Paradigms and Approaches",slug:"vector-control-some-new-paradigms-and-approaches",signatures:"Claire Duchet, Richard Allan and Pierre Carnevale",authors:[{id:"151662",title:"Dr.",name:"Pierre",middleName:null,surname:"Carnevale",fullName:"Pierre Carnevale",slug:"pierre-carnevale"},{id:"169000",title:"Dr.",name:"Richard",middleName:null,surname:"Allan",fullName:"Richard Allan",slug:"richard-allan"},{id:"169008",title:"Dr.",name:"Claire",middleName:null,surname:"Duchet",fullName:"Claire Duchet",slug:"claire-duchet"}]},{id:"43870",title:"New Salivary Biomarkers of Human Exposure to Malaria Vector Bites",slug:"new-salivary-biomarkers-of-human-exposure-to-malaria-vector-bites",signatures:"Papa M. Drame, Anne Poinsignon, Alexandra Marie, Herbert\nNoukpo, Souleymane Doucoure, Sylvie Cornelie and Franck\nRemoue",authors:[{id:"151515",title:"Dr.",name:"Papa Makhtar",middleName:null,surname:"Drame",fullName:"Papa Makhtar Drame",slug:"papa-makhtar-drame"},{id:"151648",title:"Dr.",name:"Franck",middleName:null,surname:"Remoué",fullName:"Franck Remoué",slug:"franck-remoue"},{id:"154034",title:"Dr.",name:"Anne",middleName:null,surname:"Poinsignon",fullName:"Anne Poinsignon",slug:"anne-poinsignon"},{id:"154035",title:"MSc.",name:"Alexandra",middleName:null,surname:"Marie",fullName:"Alexandra Marie",slug:"alexandra-marie"},{id:"154037",title:"Dr.",name:"Souleymane",middleName:null,surname:"Doucoure",fullName:"Souleymane Doucoure",slug:"souleymane-doucoure"},{id:"154038",title:"MSc.",name:"Herbert",middleName:null,surname:"Noukpo",fullName:"Herbert Noukpo",slug:"herbert-noukpo"},{id:"154039",title:"Dr.",name:"Sylvie",middleName:null,surname:"Cornélie",fullName:"Sylvie Cornélie",slug:"sylvie-cornelie"}]},{id:"44149",title:"Transgenic Mosquitoes for Malaria Control: From the Bench to the Public Opinion Survey",slug:"transgenic-mosquitoes-for-malaria-control-from-the-bench-to-the-public-opinion-survey",signatures:"Christophe Boëte and Uli Beisel",authors:[{id:"98400",title:"Dr.",name:"Christophe",middleName:null,surname:"Boëte",fullName:"Christophe Boëte",slug:"christophe-boete"},{id:"167749",title:"Dr.",name:"Uli",middleName:null,surname:"Beisel",fullName:"Uli Beisel",slug:"uli-beisel"}]}]}]},onlineFirst:{chapter:{type:"chapter",id:"72563",title:"Contribution of Gut Microbiome to Human Health and the Metabolism or Toxicity of Drugs and Natural Products",doi:"10.5772/intechopen.92840",slug:"contribution-of-gut-microbiome-to-human-health-and-the-metabolism-or-toxicity-of-drugs-and-natural-p",body:'
1. Introduction
The human gastrointestinal tract has various microorganisms, and “gut microbiota” has received attentions recently because the microbe population living in human intestine has significant effects to human health. Gut microbiota plays important roles in human, involving in many activities in a host body, for example, metabolism of xenobiotic compounds, immune system, nutrition, inflammation, and behavior. The delivery of prebiotics and probiotics to the human gastrointestinal tract, via dietary products or supplements, is one of the tools for management of microbiota in order to improve host health [1]. Moreover, gut microbiome has interactions with drugs and natural products, producing metabolites, which give effects on efficacy, metabolism, and toxicity of drugs. Gut microbiota plays a role in the metabolism of drugs and natural products, as well as nutrients in diet or food. The conversion of a dietary soybean isoflavone, daidzein (1) or genistein (2), to a bioactive compound, S-equol (3) (Figure 1) [2, 3], is a good example for the role of gut bacteria in the production of pharmacologically active agent in human because S-equol (3) is a potent ligand for estrogen receptor β [4]. Daidzein (1) is also derived from its corresponding isoflavone glycoside, daidzin (4), by Bifidobacterium, a representative of major bacterial species of human origin; this bacterium could transform daidzin (4) to daidzein (1) by cell-associated β-glucosidases (Figure 1) [5]. Moreover, O-desmethylangolensin (5) is also found as an intestinal bacterial metabolite of daidzein (1) [6, 7].
Figure 1.
Bioconversion of soybean isoflavones, daidzein (1), genistein (2), and daidzin (4), to S-equol (3) and O-desmethylangolensin (5) by intestinal bacteria.
The transformation of achiral molecule daidzein (1) to a chiral molecule equol, which has one chiral center in its molecule, should provide two possible enantiomers of S-equol (3) and R-equol (3R) (Figure 2). However, gut bacteria selectively gives only S-equol (3), not R-equol (3R); this is interesting because only S-equol (3) has a high affinity to bind with estrogen receptor β, while R-equol (3R) has much less activity [4]. Therefore, S-equol (3), but not R-equol (3R), has high affinity for estrogen receptor β in human, and S-equol (3) has more potent estrogenic activity than estradiol [4]. In animal model, although a mixture of the two enantiomers of equol have the ability to inhibit bone loss in ovariectomized mice [8], S-equol (3) has better inhibitory effects on bone fragility than the racemic mixture containing both S-equol (3) and R-equol (3R) [9].
Figure 2.
Structures of two enantiomers of S-equol (3) and R-equol (3R) and the bioconversion of daidzein (1) to S-equol (3) by the bacterium Lactococcus sp. through the metabolites (R)-dihydrodaidzein (6), (S)-dihydrodaidzein (7), and trans-tetrahydrodaidzein (8).
The ability of gut bacteria to selectively produce the correct bioactive isomer of S-equol (3) needed for human is intriguing. Shimada and co-workers identified enzymes involved in the bioconversion of daidzein (1) to S-equol (3) by the bacterium Lactococcus sp. strain 20–92, which was isolated from feces of healthy human [10]. The enzyme daidzein reductase catalyzes the transformation of daidzein (1) to (R)-dihydrodaidzein (6), which is in turn converted to (S)-dihydrodaidzein (7) by the enzyme dihydrodaidzein racemase (Figure 2). The enzyme dihydrodaidzein reductase catalyzes the conversion of (S)-dihydrodaidzein (7) to trans-tetrahydrodaidzein (8), which is converted to S-equol (3) by the enzyme tetrahydrodaidzein reductase [10]. The bioconversion of daidzein (1) selectively to S-equol (3), not R-equol (3R), by gut bacteria provides human the correct enantiomer for binding with estrogen receptor β; this may be host-bacterial mutualism in human intestine. An isoflavone daidzein (1) is found in leguminous plants such as soybeans and other legumes, which have been used as food for human since ancient times. Therefore, it is possible that gut bacteria have experienced with daidzein (1) long time ago, and their enzymatic evolutions lead to the selective bioconversion of daidzein (1) to S-equol (3), which has biological activity for human. Interestingly, many studies revealed that there is the intestinal microbiota-to-host relationship, i.e., a cross talk, between gut microbiota and human host and interactions between gene products from the microbiome with metabolic systems of human diseases such as obesity and diabetes [11].
The conversion of a dietary soybean isoflavone, daidzein (1) or genistein (2), to S-equol (3), by gut bacteria has been known for many years; however, scientists might not be aware of the importance of gut microorganisms in the past. Recently, a number of studies have revealed many essential roles of gut microbiota in human health and diseases. Gut microbiome can transform nutrients and dietary fibers to produce bioactive metabolites, for example, short-chain fatty acids (SCFAs) and nicotinamide, which have a significant impact on human health and diseases. There have been reports on interactions of gut microbiome and compounds, e.g., drugs and natural products, after humans take these compounds as drugs for the treatment of diseases. The metabolites obtained from the metabolism of drugs/natural products by the activities of gut microbiome have either positive or negative effects on therapeutic efficiency. This chapter provides the information of recent studies on the influence of the metabolites produced by gut microbiome on human health and diseases and on the interactions of microbiome and drugs/natural products.
2. Contributions of metabolites produced by gut microbiome to human health and diseases
The human gastrointestinal tract has trillions of microorganisms with a complex and diverse community. Gut microbiome is recognized as an “organ” because gut microorganisms have metabolic activities similar to an organ and have several essential functions to human health [12]. It is estimated that microbial cells in the human body are 10 times more than human cells and that gut microbiome has 150 times more genes than human genome [13]. Perturbation of gut microbial communities leads to the imbalance of gut microorganisms, by either reducing or increasing particular microbial species or altering the relative abundance of certain microorganisms; this is collectively known as “dysbiosis.” Microbial dysbiosis can cause certain diseases such as irritable bowel syndrome, diabetes, cancer, inflammatory bowel diseases, and obesity [14, 15, 16]. Gut microorganisms are able to produce many metabolites, which give substantial contributions to human health because they are involved in various physiological processes, i.e., host immunity, cell-to-cell communication, and energy metabolism [17, 18]. The metabolites produced by gut microbiome are linked with human diseases, for example, colorectal cancer [19], depression [20], inflammation and cancer [21], and cardiovascular and metabolic diseases [22, 23]. Among the metabolites produced by gut microbiome, SCFAs considerably play critical roles in human health. Gut microbiome produces acetate (9), propionate (10), and butyrate (11) (Figure 3), the respective conjugate bases of acetic acid, propionic acid, and butyric acid; these SCFAs are from saccharolytic fermentation of dietary fibers by gut microorganisms [24]. Butyrate (11) from the metabolism of gut microbiome could induce differentiation of colonic regulatory T cells in mice, suggesting that gut microorganisms are substantially involved in immunological homeostasis in the gastrointestinal tract of human [25]. SCFAs produced by gut microbiota are significantly linked with hypertension and kidney diseases [26]. SCFAs are vital fuels for intestinal epithelial cells and can maintain intestinal homeostasis; they are involved in the regulation of gut epithelial cells and immunity that is relevant to inflammatory bowel diseases [27, 28]. SCFAs are able to activate G-protein-coupled receptor, for example, GPR43, which has a role in intestinal inflammatory diseases, i.e., inflammatory bowel diseases [29]. Moreover, SCFAs produced by gut microbiome are energy source for colonocytes and can inhibit histone deacetylases, the enzymes catalyzing the removal of acetyl groups from the lysine residue of histone [30]. Recent study revealed that butyrate (11) from the metabolism of gut microbiome could promote histone crotonylation in colon epithelial cells and that the reduction of the gut microbiota leads to many changes in histone crotonylation in the colon [31].
Figure 3.
Structures of SCFAs including acetate (9), propionate (10), and butyrate (11).
Recent study revealed that SCFAs produced by gut microbiome had relationships with metabolic diseases [32]. The level increase of butyrate (11) (Figure 3) by gut microbiome can improve insulin response after an oral glucose tolerance test; moreover, the defects in the production or absorption of propionate (10) led to an increased risk of type 2 diabetes [32]. Previous study also demonstrated that type 2 diabetes is linked with changes in the composition of gut microbiome because the profile of gut microorganisms in human with type 2 diabetes is different from that without type 2 diabetes (a control group) [33]. SCFAs are known to have a significant impact on the energy homeostasis, i.e., controlling the energy metabolism; therefore, modulation of SCFAs could be a nutritional target to prevent diseases associated with metabolism disorders, for example, type 2 diabetes and obesity [34]. Gut microbiome is also linked with food allergy in human, and changes in the population and composition of gut microbiota might cause food allergy [35], and the use of gut microbiome is a potential innovative strategy to prevent food allergy in human [36]. In an animal model, certain gut bacteria, e.g., Clostridia species, might be useful for prevention or therapy of food allergy [37]. Recent investigation led by Nagler showed that butyrate (11) (Figure 3) produced by the gut bacterium, Anaerostipes caccae, could contribute to the prevention of milk allergy in children [38]. Germ-free mice colonized with bacteria in feces of healthy infants can protect mice against milk allergy, while those colonized with bacteria in feces of milk allergic infants could not protect mice from milk allergy; this result indicates that gut microbiotas are involved in milk allergy. Detailed analysis revealed that compositions of gut bacteria in healthy infants were different from milk allergic infants, and the gut bacterium, A. caccae, was the key agent to protect against an allergic response to food [38]. A. caccae is a saccharolytic intestinal bacterium producing butyrate (11) [39]. It is known that butyrate (11) is a key energy source for colonic epithelial cells, regulating energy metabolism and autophagy in the mammalian colon [40]. Therefore, butyrate (11) is likely to be the key metabolite responsible for the protection of milk allergy [38]. An independent study revealed that a dietary supplemented with the bacterium Lactobacillus rhamnosus could promote tolerance in infants with cow’s milk allergy by enrichment of butyrate-producing bacterial strains [41]. The increased levels of butyrate (11) in feces of infants who received the supplement with L. rhamnosus were observed in the most tolerant infants against milk allergy [41].
Nicotinamide (12) is an amide derivative of vitamin B3 or niacin or nicotinic acid (13) (Figure 4) and is a substrate for nicotinamide adenine dinucleotide (NAD), a coenzyme in many important enzymatic oxidation–reduction reactions, for example, electron transport chain, citric acid cycle, and glycolysis. Nicotinamide (12) is known to have a role in neuronal systems in the central nervous system, thus implicating in neuronal death and neuroprotection [42]. Recent study led by Elinav revealed that nicotinamide (12) produced by the gut bacterium, Akkermansia muciniphila, significantly protected the progression of the neurodegenerative disease, amyotrophic lateral sclerosis (ALS) [43]. The experiment demonstrated that removal of gut microorganisms by treating mice with antibiotics could promote the ALS symptoms in mice, indicating that gut microbiome modulated the progress of ALS disease [43]. The study showed that the species of gut bacteria in healthy human were different from that in ALS patients; A. muciniphila was abundant in healthy people, while Ruminococcus torques and Parabacteroides distasonis were relatively abundant in ALS patients. Remarkably, transplantation of gut bacteria from human gut to germ-free mice revealed that the gut bacterium A. muciniphila improved the ALS symptoms, while the gut bacteria R. torques and P. distasonis worsened the ALS symptoms [43]. Detailed analysis found that the gut bacterium A. muciniphila provided nicotinamide (12) as a bioactive metabolite that improves the ALS symptoms. Indeed, a direct injection of nicotinamide (12) into mice with ALS could improve a motor-neuron function. The study in 37 patients with ALS revealed that the levels of nicotinamide (12) in cerebrospinal fluid of ALS patients were lower than that in people without ALS. Moreover, analysis of microbial genes involved in nicotinamide synthesis in feces of ALS patients revealed that people with ALS had less number of the genes for nicotinamide synthesis; these genes were mainly from the gut bacterium A. muciniphila. Therefore, it is likely that ALS patients might have less abundance of A. muciniphila in their gastrointestinal tract [43]. This work suggests that gut microbiome has a significant link with human disease pathophysiology and that there is an opportunity to use microbial therapeutic targets for certain diseases. Indeed, a clinical trial on human using the gut bacterium, A. muciniphila, in overweight and obese insulin-resistant volunteers demonstrated that the gut bacterium could reduce insulin resistance indices and could lower the levels of circulating insulin and blood cholesterol, thus improving the profile of blood lipid and insulin sensitivity [44]. This microbial therapeutic approach is safe and may be applied for the treatment of overweight or obese insulin-resistant people.
Figure 4.
Structures of nicotinamide (12) and niacin or nicotinic acid (13).
It is known that gut microbiota is significantly associated with autism spectrum disorder, a form of mental disorder with difficulties in social communication and interaction [45]. Intriguingly, a recent study led by Sharon and Mazmanian revealed that gut microbiota could produce neuroactive metabolites which contribute to the pathophysiology of autism spectrum disorder, thus regulating behaviors in mice [46]. The experiment showed that germ-free mice receiving gut microbiota from human donors with autism spectrum disorder could induce autistic behaviors in mice. The metabolites produced by gut bacteria, 5-aminovaleric acid (14) and taurine (15) (Figure 5), were found to modulate behaviors related to autism spectrum disorder. Both 5-aminovaleric acid (14) and taurine (15) are GABAA receptor agonists [47, 48]. Levels of 5-aminovaleric acid (14) in mice with autism spectrum disorder were significantly lower than that in the control mice, while levels of taurine (15) in mice with autism spectrum disorder were ca. 50% less than the control group [46]. Administration of 5-aminovaleric acid (14) and taurine (15) to mice with autism spectrum disorder could improve repetitive and social behaviors, i.e., modulating neuronal excitability in mice brain and improving behavioral abnormalities [46]. This finding suggests that autism spectrum disorder is also related to the influence of gut microbiota; therefore microbiome interventions using fecal microbiota transplantation, as well as supplementation with metabolites produced by gut microorganisms or with probiotics, may improve the quality of life for people with autism spectrum disorder.
Figure 5.
Structures of 5-aminovaleric acid or 5-aminopentanoic acid (14) and taurine or 2-aminoethanesulfonic acid (15).
Gut microbiome substantially contributes to human health and diseases, and the metabolites produced by gut microbiome mentioned earlier underscore the importance of gut microorganisms in health and certain diseases in human. Health and diseases of individuals partly rely on the conditions of gut microbiome whether they have healthy gut microbiota or unhealthy ones. Gut microbiota is therefore considered as a “hidden” or “forgotten” human organ [12], involving in pathology of Alzheimer’s disease [49], endocrine organ involving metabolic diseases [50], and chronic gastrointestinal disease [51]. Moreover, gut microbiota is also considered as an “invisible” organ that controls and manipulates the function of drugs [52]. The imbalance of gut microbiota, or known as dysbiosis, leads to unhealthy conditions for human or even causes certain diseases. Therefore, the use of gut microbiota as a therapeutic target for treatments of human diseases is an emerging approach for many diseases, for example, Parkinson’s disease [53], cardiovascular disease [54], metabolic disorders [55], hepatocellular carcinoma [56], nonalcoholic fatty liver disease [57], food allergy [58], and heart failure [59]. Supplementation with probiotics or with health-promoting bacteria is a possible therapeutic method and may widely be used in the near future. Fecal microbiota transplantation or supplementation with metabolites from gut microorganism needs more clinical studies; the two approaches will be a challenging research on gut microbiota in the near future.
3. Interactions of gut microbiome and drugs and/or natural products
It is estimated that a total mass of bacteria in the human body is around 0.2 kg (for people with a weight of 70 kg) and that the densities of commensal microorganisms in the human gastrointestinal tract ranged from 108 to 1011 bacterial cells/g [60]. Oral administration of drugs delivers drugs to the gastrointestinal tract that contains high densities of gut microorganisms, which could encode 150-fold more genes than those of the human genome [61]; therefore, gut microbes are able to encode many enzymes with drug-metabolizing potential [62]. Gut microbiota is recognized as an “invisible organ” responsible for controlling drug functions and modulation of drug metabolism processes [52]. Normally, antibiotic drugs give direct effects toward microorganisms in the human gastrointestinal tract, providing either negative or positive (beneficial) effects to the composition of gut microbiota [63]. However, intestinal microbiota have many important roles in maintenance of human health; therefore, perturbation of gut microbiome by antibiotics could give negative impact to human, for example, loss of colonization resistance that can prevent invading microorganisms colonizing in the human gastrointestinal tract [64]. In addition to antibiotic drugs, a recent study led by Typas demonstrated that nonantibiotic drugs also gave extensive impact on human gut bacteria because around 24% of 1197 drugs showed antibacterial activity toward at least one strain of gut bacteria [65]. This is considered as “antibiotic-like side effects” of nonantibiotic drugs, which could potentially promote antibiotic resistance that is one of the major public health problems worldwide. This finding provides essential information for drug discovery research, i.e., addressing a potential new side effect of drugs and repurposing of nonantibiotic drugs as antibacterial agents.
The next sections will highlight the interactions of gut microbiome, especially the chemistry of the drug metabolites produced by gut microorganisms, toward certain drugs and natural products. The metabolism of drugs or natural products by gut microbiome could lead to the production of bioactive metabolites, which have either beneficial effects or negative properties (i.e., reducing efficacy of drugs or natural products). The study on the interactions of gut microbiota and drugs or natural products as part of drug development process is discussed in the next sections.
3.1 Interactions of gut microbiome and commonly used drugs
Once drugs enter the human gastrointestinal tract, they encounter trillions of microorganisms, which are able to encode 150-fold more genes than human genome [61]. A number of enzymes encoded by gut microbial genes catalyze the biotransformation of drugs, producing bioactive metabolites, which have effects on human health [60]. Advances in liquid chromatography-mass spectrometry (LC–MS) technology allow the identification of the metabolites produced by gut microbiome, as well as detailed study of pharmacokinetics of drugs and their metabolites, while genome sequencing substantially assists the identification of genes encoding enzymes in gut microorganisms. Zimmermann and co-workers investigated the drug metabolism of an antiviral nucleoside drug, brivudine (16), which is used for the treatment of herpes zoster virus; the study was performed using mice inoculated with mutant microbiota [66]. It was found that the bioconversion of brivudine (16) to bromovinyluracil (18) (or 5-(E)-(2-bromovinyl)uracil) was achieved by enzymes from both mammalian cells and gut microbial communities isolated from mice, suggesting that both host and microbiota are capable of such biotransformation (Figure 6). Previously, intestinal anaerobic bacteria were found to convert another antiviral drug, sorivudine (17), to bromovinyluracil (18) (Figure 6) [67].
Figure 6.
Biotransformation of antiviral drugs brivudine (16) and sorivudine (17) to bromovinyluracil (18) by gut bacteria.
Gut bacteria, Bacteroides thetaiotaomicron and B. ovatus, were the major species having the highest metabolic activity to convert brivudine (16) to bromovinyluracil (18) [66]. Comparison of serum kinetics of brivudine (16) and bromovinyluracil (18) in conventional (a control with bacteria) and germ-free mice after feeding with the drug brivudine (16) suggested that intestinal bacteria contributed to the amount of bromovinyluracil (18) in serum because the level of bromovinyluracil (18) in conventional mice serum was five times higher than that of germ-free mice [66]. The gene, bt4554, encoding the enzyme purine nucleoside phosphorylase necessary for the metabolism of brivudine (16) is present in B. ovatus and conserved in the bacterial phylum Bacteroidetes; the expression of the gene bt4554 is a rate-limiting step [66]. The gut bacterium, B. thetaiotaomicron, was found to completely metabolize the drug brivudine (16) to bromovinyluracil (18), which is absorbed from both the cecum and colon. This study was also able to predict the levels in serum and sources of the metabolite bromovinyluracil (18) derived from a drug sorivudine (17) (Figure 6) [66].
Zimmermann and co-workers also used clonazepam (19) (Figure 7), an anticonvulsant and antianxiety drug, as a model [66]; the metabolism of this drug in rats gave metabolic products through nitroreduction, oxidation, glucuronidation, and enterohepatic cycling [68]. After an oral administration of a drug clonazepam (19) to mice, 7-NH2-clonazepam (20) and 7-NH2-3-OH-clonazepam (21) were found as major metabolites in serum of the conventional mice (Figure 7). The host-microbiome pharmacokinetic model revealed that 7-NH2-clonazepam (20) in serum was substantially from a microbial contribution. Experiments also revealed that intestinal microbes could convert glucuronyl-3-OH-clonazepam (23) to 3-OH-clonazepam (22), which in turn transformed to 7-NH2-3-OH-clonazepam (21) by microbial reduction (Figure 7) [66]. The study established a pharmacokinetic model that can predict microbiome or host (human) contributions to drug metabolism, e.g., the ability to distinguish drug-metabolizing activity by human or gut bacteria [66]. This research model is particularly useful for the study on drug metabolism in an animal model.
Figure 7.
Biotransformation of clonazepam (19) to the metabolites 20–23 by human intestinal microbes.
Gut microbiome has potential ability to metabolite many drugs, thus affecting the therapeutic efficacy due to lower concentrations of drugs. The study on the drug metabolism of 271 commonly used drugs by gut bacteria revealed that, after incubation of drugs with gut bacteria, the levels of 176 drugs (accounting for two thirds of 271 drugs) were significantly reduced, indicating that these drugs were metabolized by gut bacteria [62]. Intriguingly, each bacterial strain (from 76 human gut bacterial strains) could metabolize up to 11–95 drugs [62]. This result suggests that, when designing the drug molecules, the drug metabolism by gut microbes should be seriously considered, particularly the drugs delivered by an oral administration. Therefore, the action of gut microbiome toward individual drug candidates should also be evaluated during the drug development process. Untargeted metabolomics analysis is used to identify products derived from drug metabolism by gut bacteria, and it could properly identify the metabolites from microbial metabolism of drugs [62]. Some drugs, for example, paliperidone, sulfasalazine, and pantoprazole, were previously investigated for their metabolism by gut microbes [69]. Detailed analysis by high-resolution mass spectrometry (HRMS) revealed that drugs with an acetyl ester or an alkene functional group, such as norethisterone acetate (24), drospirenone (25), and roxatidine acetate (26), were metabolized through either deacetylation (removing C2H2O) or hydrogenation (adding H2) by gut bacteria (Figure 8) [62]. Gut bacteria metabolized drugs with aliphatic hydroxyl or amine functional group such as dasatinib (27), fluphenazine (28), and primaquine (29) through propionylation (adding C3H4O), giving their corresponding O- or N-propionyl products 30, 31, and 32, respectively (Figure 8). The HRMS data clearly indicated the mass difference of 56.026 unit of a propionyl group between the drug and its corresponding derivative [62].
Figure 8.
Structures of the drugs, norethisterone acetate (24), drospirenone (25), and roxatidine acetate (26) and biotransformation of dasatinib (27), fluphenazine (28), and primaquine (29) to their corresponding products 30, 31, and 32, respectively, by gut bacteria.
Zimmermann and co-workers investigated the metabolism of drug in mice model and in human gut microbial communities using a corticosteroid drug, dexamethasone (33), as a model (Figure 9) [62]. It is known that this class of drug is metabolized by the bacterium Clostridium scindens through the side-chain cleavage, known as the desmolytic activity, to produce the active androgen form of the drug, dexamethasone-desmo (34) (Figure 9) [70, 71]. Levels of dexamethasone-desmo (34) were measured after an oral administration of dexamethasone (33) to germ-free mice and to mice that have only one bacterial species of C. scindens, technically known as gnotobiotic mice (GNC. scindens). Although dexamethasone (33) was found in the cecum of germ-free mice and gnotobiotic mice, the levels of the drug were significantly reduced in gnotobiotic mice, suggesting that the bacterium C. scindens associated in these mice is involved in the drug metabolism. Accordingly, levels of the androgen form of the drug, dexamethasone-desmo (34), which are derived from the metabolism of dexamethasone (33), were higher in both serum and cecum of gnotobiotic mice than that of germ-free mice [62]. Moreover, similar corticosteroid drugs, i.e., prednisone (35), prednisolone (36), cortisone (37), and cortisol (38), were also metabolized by the intestinal bacterium C. scindens through the desmolytic activity, giving the metabolite products of prednisone-desmo (39), prednisolone-desmo (40), cortisone-desmo (41), and cortisol-desmo (42), respectively (Figure 9). However, when incubating the drug dexamethasone (33) with gut bacterial community isolated from 28 healthy human participants under anaerobic condition, the drug-metabolizing activity had considerable interpersonal variation as suggested by level variations of the drug metabolite, dexamethasone-desmo (34) [62]. This result implies that dexamethasone (33) is also metabolized by other gut bacterial species, not only C. scindens.
Figure 9.
Gut bacterial metabolism of corticosteroid drugs, dexamethasone (33), prednisone (35), prednisolone (36), cortisone (37), and cortisol (38), to their respective products 34, 39, 40, 41, and 42 via the desmolytic activity.
Systematic identification of drug-metabolizing genes encoded by gut bacteria provides the mechanistic insights into drug metabolism in human [62]. Genes of the gut bacterium Bacteroides thetaiotaomicron were cloned into Escherichia coli, leading to the identification of new 16 gene products, which were able to metabolite 18 drugs to 41 different metabolites [62]. Certain gene products have specificity and cross-activity, and gene deletion and complementation techniques revealed the mechanisms of individual gene products. For instance, the bt2068 gene encodes the enzyme that could reduce (adding H2) norethisterone acetate (24) (Figure 8), as well as other similar steroid drugs such as levonorgestrel and progesterone, while the bt2367 gene encodes acyltransferase that converts the drug pericyazine (43) to both acetyl- and propionyl-pericyazine products, e.g., acetyl-O-pericyazine (44) and propionyl-O-pericyazine (45), respectively (Figure 10) [62]. It is known that the metabolism products of a drug diltiazem (46) are N-desmethyldiltiazem (47), N,N-didesmethyldiltiazem (48), O-desmethyldiltiazem (49), N,O-didesmethyldiltiazem (50), desacetyldiltiazem (51), desacetyl-N-desmethyldiltiazem (52), desacetyl-N,N-didesmethyldiltiazem (53), desacetyl-O-desmethyldiltiazem (54), and desacetyl-N,O-didesmethyldiltiazem (55) (Figure 10) [72]. The gene bt4096 in gut bacteria is responsible for the deacetylation of diltiazem (46) and its metabolites 47–50 to give their corresponding deacetylated products 51–55, respectively (Figure 10) [62]. This study suggests that gut bacteria substantially contribute to drug metabolism in the human gastrointestinal tract, and the metabolism of drug candidates by gut microbiome should be studied as a part of the drug development processes.
Figure 10.
Metabolism of pericyazine (43) to acetyl-O-pericyazine (44) and propionyl-O-pericyazine (45) and metabolism of diltiazem (46) to the metabolite products 47–55 by gut bacteria.
The drug metabolism by gut microbiome can give negative effects to drug efficacy, thus leading to the decrease in efficiency and potency of certain drugs. L-dopa or levodopa (56) (Figure 11) is the first-line drug for the treatment of Parkinson’s disease; the metabolism of this drug by gut microbiome provides negative effects for Parkinson’s patients. The drug L-dopa (56) can cross the blood–brain barrier, entering the central nervous system and then transforming to a neurotransmitter, dopamine (57), by the enzyme pyridoxal phosphate l-amino acid decarboxylase (Figure 11). It is known that intestinal microflora (gut microbiome) can metabolite L-dopa (56) [73] and that the formation of m-tyramine (58) from L-dopa (56) is a side effect of this drug for parkinsonism (Figure 11) [74]. A neurotransmitter, dopamine (57), is the only active agent needed for the treatment of parkinsonism, and it should be formed from L-dopa (56) at the central nervous system after L-dopa (56) crossing the blood–brain barrier. However, the generation of dopamine (57) from the drug L-dopa (56) can occur at the human gastrointestinal tract (known as peripheral metabolism), not at the central nervous system, thus giving undesirable side effects. To prevent this peripheral metabolism, an inhibitor of pyridoxal phosphate l-amino acid decarboxylase, carbidopa (59) (Figure 11), is coadministered with the drug L-dopa (56). It is known for many years that microorganisms can decarboxylate L-dopa (56) to dopamine (57), which in turn undergoes the dehydroxylation reaction to give m-tyramine (58) [75]. The treatment of L-dopa (56) is improved when patients receive broad-spectrum antibiotics, which suppress the growth of gut bacteria, indicating that gut bacteria are involved in the decrease of therapeutic efficiency of L-dopa (56) [76]. Therefore, gut microbiome can potentially reduce the drug efficacy of L-dopa (56) through their metabolic activities toward the drug.
Figure 11.
Bioconversion of L-dopa (56) to dopamine (57) and m-tyramine (58) by gut bacteria and structures of inhibitors of amino acid decarboxylases, carbidopa (59), (S)-α-fluoromethyltyrosine (60), benserazide (61), and methyldopa (62).
Recent study led by Prof. Balskus revealed that the gut bacterium Enterococcus faecalis has the tyrDC gene encoding the enzyme tyrosine decarboxylase that is able to decarboxylate both L-dopa (56) and an amino acid, tyrosine [77]. Moreover, the gut bacterium Eggerthella lenta has the dadh gene encoding a molybdenum cofactor-dependent dopamine dehydroxylase, which is the enzyme responsible for the dehydroxylation of dopamine (57) to m-tyramine (58) (Figure 11). The metabolism of L-dopa (56) and dopamine (57) in complex gut microbiotas of Parkinson’s patients is dependent on the tyrDC and dadh genes [77]. The study demonstrated that carbidopa (59), an inhibitor of pyridoxal phosphate l-amino acid decarboxylase, failed to prevent L-dopa (56) metabolism in complex gut microbiotas of Parkinson’s patients [77]. However, another inhibitor, (S)-α-fluoromethyltyrosine (60) (Figure 11), could prevent the decarboxylation of L-dopa (56) that is from the metabolic activities of both the bacterium E. faecalis and complex gut microbiotas of Parkinson’s patients [77]. In a mouse model, levels of the drug L-dopa (56) increased in serum when coadministered (S)-α-fluoromethyltyrosine (60) with L-dopa (56) to mice colonized with the gut bacterium E. faecalis [77]. An independent study led by Prof. Aidy also identified the tdc gene responsible for tyrosine decarboxylases in the gut bacterium E. faecium; bacterial tyrosine decarboxylases efficiently convert the drug L-dopa (56) to dopamine (57) [78]. Aidy and co-workers also found that carbidopa (59) in L-dopa (56) combination therapy did not inhibit the activities of decarboxylase enzymes in gut bacteria, E. faecalis and E. faecium [78]. Moreover, other decarboxylase inhibitors, benserazide (61) and methyldopa (62) (Figure 11), also failed to inhibit the decarboxylase activity of gut bacteria toward the drug L-dopa (56). These studies demonstrated gut microbiota significantly reduced the levels of the drug L-dopa (56) in a body, thus contributing to the higher dosages required for the Parkinson’s patients that have gut microbiome with high metabolism toward the drug L-dopa (56). Variations in gut microbiota among Parkinson’s patients might contribute to the different responses, i.e., harmful side effects and decreased efficacy, to the drug L-dopa (56). Therefore, gut microbiota plays a critical role in the drug metabolism and considerably contributes to treatment outcomes of this drug.
Gut microbiota can improve therapeutic efficiency of certain drugs for particular treatments. Cancer immunotherapy is relatively new for cancer treatment using human immune system to control and eradicate cancer cells, and it is more precise and personalized, thus providing more effectiveness with fewer side effects than other cancer treatments. Gut microbiota was found to play a role in cancer immunotherapy targeting CTLA-4, a protein receptor downregulating the immune system, because anticancer effects of CTLA-4 blockade were found to depend on gut bacteria of Bacteroides species, e.g., Bacteroides thetaiotaomicron or B. fragilis [79]. The study demonstrated that germ-free mice did not show the response to CTLA blockade, thus defecting an anticancer property of the drug. Indeed, this drug deficiency could be improved by gavage with the gut bacterium B. fragilis through immunization with the bacterium polysaccharides or by adoptive transfer of B. fragilis-specific T cells. Therefore, this research study demonstrates that the gut bacterium could help patients treated with a monoclonal antibody drug for the treatment of cancer targeting CTLA-4 [79].
Gut microbiome also improves therapeutic effect of a cancer immunotherapy targeting immune checkpoint inhibitor via the PD-1/PD-L1 pathway [59]. Antibiotics are found to give negative effects for patients treated with cancer immunotherapies as they inhibit the efficacy of immune checkpoint inhibitor drug that targets the programmed cell death receptor of the PD-1/PD-L1 pathway [59]. Moreover, suppression of growth of gut bacteria by antibiotic drugs leads to the decrease of drug efficacy, suggesting that gut microorganisms are important for this cancer therapy. The study demonstrated that gut microbiota provided significant effects on cancer immunotherapies targeting the PD-1/PD-L1 interaction because there was substantial association between commensal microorganisms and therapeutic response of anticancer drug that inhibits the activity of PD-1 and PD-L1 immune checkpoint proteins [80]. Gut bacteria including Collinsella aerofaciens, Enterococcus faecium, and Bifidobacterium longum were found to be associated with the improvement of this cancer immunotherapy. Intriguingly, reconstitution of germ-free mice with fecal samples from patients with good drug response could help to control tumor, leading to better efficacy of anti-PD-L1 cancer therapy [80]. An independent study revealed that the gut bacterium Akkermansia muciniphila assists cancer immunotherapy targeting the PD-1/PD-L1 interaction toward epithelial tumors [81]. The study on fecal microbiota transplantation demonstrated that germ-free or antibiotic-treated mice receiving gut bacteria from patients with good response to cancer immunotherapy have significant therapeutic improvement, while those receiving the samples from nonresponding patients do not have such improvement for cancer immunotherapy [81]. Restoration of the drug efficacy in germ-free mice receiving the samples from nonresponding patients was simply achieved by oral supplementation with the gut bacterium A. muciniphila, indicating the benefit of gut microbiota for this cancer immunotherapy. Another independent research also found similar benefits of gut microbiota on anti-PD-1 immunotherapy in melanoma patients; this study investigated microbiome samples from 112 patients with metastatic melanoma and found that there were substantial differences in the composition and diversity of gut microbiome obtained from patients with good drug response and from nonresponding patients [82]. Patients with good response to immunotherapeutic PD-1 blockade have abundance of gut bacteria of the family Ruminococcaceae and Faecalibacterium, while patients with poor response to immunotherapeutic PD-1 blockade tend to have relative abundance of Bacteroidales. It is possible that patients with a favorable gut microbiome, e.g., Ruminococcaceae and Faecalibacterium, toward the immunotherapeutic PD-1 blockade therapy have improved systemic and immune responses mediated by certain factors such as improvement of effector T cell function in the periphery, increase of antigen production, and improvement of the tumor microenvironment [82].
Gut microbiota also has an important role in chemotherapy for cancer treatment because they can modulate drug efficacy, for example, eliminating the anticancer properties of the drug or mediating toxicity [83]. Cyclophosphamide (63) (Figure 12) is a drug used in cancer chemotherapy for many types of cancers, as well as for autoimmune diseases, and its mechanism is through the stimulation of anticancer immune responses. In a mouse model, the composition of gut microbiota is changed after administration of cyclophosphamide (63), and this drug induces the translocation of certain Gram-positive bacteria into secondary lymphoid organs. Gut bacteria could stimulate certain immune responses beneficial to cancer therapy. Germ-free mice carrying tumor treated with antibiotics to kill Gram-positive bacteria had less therapeutic response, and their tumors exhibited resistance to the drug cyclophosphamide (63), suggesting that gut microbiota improves anticancer immune response [84]. Gut bacteria, Enterococcus hirae and Barnesiella intestinihominis, were found to help cyclophosphamide-induced therapeutic immunomodulatory response, thus improving the efficacy of this alkylating immunomodulatory drug [85].
Figure 12.
Structure of an anticancer drug, cyclophosphamide (63).
The research studies mentioned earlier demonstrate the interactions of drugs and gut microbiome that provide beneficial effects on cancer therapy. However, interactions of gut microbiome and drugs can also give negative influence in cancer treatment, for example, the treatment of an anticancer drug, gemcitabine (64) or 2′,2′-difluorodeoxycytidine (Figure 13), which is a derivative of cytidine nucleoside base. A research led by Straussman showed that the bacterium Mycoplasma hyorhinis was found to be the cause of gemcitabine (64) resistance in colon carcinoma models [86]. In a colon cancer mouse model, M. hyorhinis could metabolize gemcitabine (64) to the corresponding deaminated derivative, 2′,2′-difluorodeoxyuridine (65), that does not have anticancer activity (Figure 13). The conversion of gemcitabine (64) to 2′,2′-difluorodeoxyuridine (65) was previously reported [87], and the nucleoside-catabolizing enzymes, i.e., cytidine deaminase, in the bacterium, M. hyorhinis, were also identified [88]. Straussman and co-workers analyzed genes and genomes of 2674 bacterial species and found that most of the Gammaproteobacteria class had the gene coding for the enzyme cytidine deaminase, thus potentially mediating gemcitabine resistance [86]. In a mouse model of colon carcinoma, mice receiving an antibiotic, ciprofloxacin, showed a good response to the anticancer drug gemcitabine (64), indicating that suppression of the growth of certain bacteria led to the improvement of the drug efficacy. Investigation of human pancreatic ductal adenocarcinoma collected from pancreatic cancer surgery revealed that there were intratumor bacteria, mainly belonging to the class Gammaproteobacteria such as Enterobacteriaceae and Pseudomonadaceae families in these samples; the intratumor bacteria can mediate resistance to chemotherapy of the drug gemcitabine (64) [86]. Therefore, the metabolism of the drug gemcitabine (64) to 2′,2′-difluorodeoxyuridine (65) by gut microbiota provides the negative effects for cancer treatment. This study underscores the importance of the research on drug metabolism by gut microbiome, which should be investigated for the new drug candidates during the drug development processes.
Figure 13.
Biotransformation of gemcitabine (64) to its metabolite 2′,2′-difluorodeoxyuridine (65); structures of anticancer drugs, oxaliplatin (66) and fluorouracil or 5-FU (67), and autophagy lysosomal inhibitor, chloroquine (68).
Additional example for the negative effects of gut microbiota for cancer chemotherapy is the treatment of colorectal cancer with the drugs, oxaliplatin (66) and fluorouracil or 5-FU (67) (Figure 13); the gut bacterium Fusobacterium nucleatum was found to promote resistance to chemotherapy for colorectal cancer [89]. Analysis of colorectal cancer tissues collected from patients with recurrence or without recurrence of cancer revealed that the bacterium F. nucleatum is associated with the recurrence of colorectal cancer, which is derived from chemoresistance toward the drugs [89]. Cultivation of colorectal cancer cells co-cultured with F. nucleatum revealed that the bacterium potentially activated an autophagy pathway in colorectal cancer cells. An addition of a known autophagy lysosomal inhibitor, chloroquine (68) (Figure 13), could inhibit autophagic flux in the F. nucleatum-cultured cells, confirming the autophagy activation induced by the gut bacterium F. nucleatum [89]. Moreover, this bacterium reduced cell apoptosis of colorectal cancer cells, indicating that it specifically induced resistance toward the drugs oxaliplatin (66) and fluorouracil (67). Co-cultured cancer cells with the bacterium F. nucleatum and treated cancer cells with the drugs oxaliplatin (66) and fluorouracil (67) in the presence of autophagy lysosomal inhibitor, chloroquine (68), could eradicate chemoresistant effect, strongly confirming that the bacterium F. nucleatum induced chemoresistance through the autophagy pathway [89]. Detailed mechanistic study revealed that the bacterium F. nucleatum mediated chemoresistance through the TLR4 and MYD88 signaling pathway [89]. An independent study showed that the gut bacterium F. nucleatum is a diagnostic marker of colorectal cancer because patients with this cancer generally have high density of this bacterium in tumor cells [90]. Several studies have shown the prevalence of the bacterium F. nucleatum in colorectal tissues and fecal samples of patients, and those with high density of this bacterium tend to have lower rate of survival [91]. Therefore, manipulation of the bacterial population of F. nucleatum might be useful for the treatment of colorectal cancer, and this bacterium is potentially a diagnostic and/or prognostic marker for colorectal cancer.
In addition to drug metabolism, gut microbiota is also involved in drug–drug interactions when patients take two drugs at the same time, particularly when using antibiotics together with other drugs. Several studies have demonstrated the effects of antibiotic drugs on the metabolic activities of gut microbiota toward drugs and phytochemicals [92]. An example of a drug–drug interaction is the contribution of an antibiotic drug, amoxicillin (69), to a nonsteroidal anti-inflammatory drug aspirin (70) (Figure 14) [93]. It is worth mentioning that aspirin (70) is used not only for a pain reliever but also for primary prevention of cardiovascular disease [94] and cancer chemoprevention [95]. Recent study showed that amoxicillin (69) potentially affected the composition of gut microbiota by reducing number and species of intestinal bacteria in rats; the abundance of the gut bacteria, Prevotella copri and Helicobacter pylori, was reduced significantly after rats receiving amoxicillin (69) [93]. Gut microorganisms in rats could metabolite aspirin (70) to salicylate or salicylic acid (71) (Figure 14). Salicylate is a conjugate base of salicylic acid (71). It is known that the drug aspirin (70) is not responsible for a pain relief, but its metabolite, salicylic acid (71), is the active metabolite responsible for a pain relief with anti-inflammatory effect [96]. Therefore, gut microbiota plays an important role in the biotransformation of the drug aspirin (70) into the active metabolite, salicylic acid (71). After an oral administration of an antibiotic drug amoxicillin (69) to rats, the reduction of the metabolism of aspirin (70) into salicylic acid (71) was observed, suggesting the decrease of gut microbiota by amoxicillin (69) led to the reduction of the biotransformation of aspirin (70) into salicylic acid (71). Further study on the pharmacokinetics of aspirin (70) in rats revealed that amoxicillin (69) significantly affected the pharmacokinetic properties of aspirin (70) [93]. This study indicates that changes of the composition of gut microbiome by antibiotic drugs could substantially disturb the therapeutic effect of other drugs.
Figure 14.
Structures of amoxicillin (69), aspirin (70) and its metabolite, salicylate or salicylic acid (71), and nifedipine (72).
Previous study also showed that antibiotics substantially reduced the metabolic activity of gut microbiota toward aspirin (70), leading to the reduction of an antithrombotic effect of aspirin (70) [97]. Moreover, environmental changes, e.g., high-altitude hypoxia, also give effects on the pharmacokinetics and pharmacodynamics of aspirin (70) because of the changes in gut microbiota [98]. In an animal model, the plateau hypoxic environment affected the composition of gut microbiome because it increased the bacterial species of Bacteroides in rat feces but reduced numbers of the bacteria of the genus Prevotella, Coprococcus, and Corynebacterium. Changes in gut microbiome affected the metabolism of aspirin (70), thus altering the bioavailability of aspirin (70) in patients [98]. Plateau hypoxic environment also has the effects on the drug nifedipine (72), which could be metabolized by gut microorganisms (Figure 14) [99]. Nifedipine (72) is a drug for the treatment of hypertension, precordial angina, and certain vascular diseases. Plateau hypoxic environment was found to alter the composition of gut microbiota in an animal model, thus affecting the bioavailability of nifedipine (72) [99].
Recent study led by Kittakoop revealed that valproic acid or valproate (73) (Figure 15), an anticonvulsive drug used for treatments of epilepsy and bipolar disorder, had effects on the biosynthesis of fatty acids in microorganisms including representative gut microbiome [100]. Valproic acid (73) is also an epigenetic modulator, acting as an inhibitor of histone deacetylase [101]. Initially, Kittakoop and co-workers employed “One strain many compound” (OSMAC) approach using the marine fungus Trichoderma reesei treated with an epigenetic modulator, valproic acid (73), aiming to modulate the fungus T. reesei to produce new natural products, which are secondary metabolites. However, valproic acid (73) was found to have the effects on the biosynthesis of fatty acids, which are primary metabolites, instead of natural products that are secondary metabolites [100]. The study revealed that valproic acid (73) at a concentration of 100 μM could either inhibit or induce the biosynthesis of certain fatty acids in fungi, yeast, and bacteria. Valproic acid (73) inhibited the biosynthesis of palmitoleic acid (C16:1), α-linolenic acid (C18:3), arachidic acid (C20:0), and lignoceric acid (C24:0) in the fungus Fusarium oxysporum, while it induced the production of α-linolenic acid (C18:3) in the fungus Aspergillus aculeatus [100]. The bacterium of the genus Pediococcus is commonly found as gut microbiome in humans and animals [102]; valproic acid (73) was found to inhibit the production of lignoceric acid (C24:0) in the bacterium, Pediococcus acidilactici [100]. The yeast Candida utilis was found as gut microbiome in pediatric patients with inflammatory bowel disease [103]; valproic acid (73) inhibited the biosynthesis of palmitoleic acid (C16:1) and α-linolenic acid (C18:3) in C. utilis [100]. The yeast Saccharomyces cerevisiae was previously found as a prevalent gut microbiome in human [104], and the drug valproic acid (73) was found to inhibit the production of α-linolenic acid (C18:3) in the yeast S. cerevisiae [100]. Interestingly, valproic acid (73) could induce the biosynthesis of trans-9-elaidic acid (74) (Figure 15) in the yeast Saccharomyces ludwigii [100]. In human, trans-9-elaidic acid (74) could increase intracellular Zn2+ in macrophages and inhibit β-oxidation in peripheral blood macrophages [105, 106]; this suggests that the production of trans-9-elaidic acid (74) in gut microorganisms induced by the drug valproic acid (73) may indirectly give the effects to human. Valproic acid (73) also had effects on the biosynthesis of polyketides because it substantially reduced the production of austdiol (75) (90% reduction) and quadricinctone A (76) (50% reduction) (Figure 15), which are the polyketides of the fungus Dothideomycetes sp. [100]. The biosynthesis of fatty acids is considerably similar to that of polyketides, i.e., sharing the same catalytic roles and biosynthetic precursors [107]. Therefore, the drug valproic acid (73) possibly gives effects on the biosynthetic pathways of both fatty acids and polyketides because of their biosynthetic similarities. Gut microbes have biosynthetic gene clusters involving in the biosynthesis of many bioactive natural products including polyketides [108]; some natural products produced by gut microbiome have biological activities. This study suggests that commonly used drugs could potentially give the effects on the biosynthesis of secondary metabolites (natural products) of gut microbiome.
Figure 15.
Structures of valproic acid or valproate (73), trans-9-elaidic acid (74), austdiol (75), and quadricinctone A (76).
3.2 Interactions of gut microbiome and natural products
Traditional medicine and natural products have significant interactions with gut microbiome. Many studies revealed that dietary natural products modulating gut microbiota are useful for prevention and management of diabetes mellitus [109]. Recent study revealed that a traditional Chinese herbal formula and an antidiabetic drug, metformin (77) (Figure 16), could improve the treatment of type 2 diabetes with hyperlipidemia by enriching certain beneficial species of gut bacteria, for example, Faecalibacterium sp. and Blautia [110]. The study was carried out in 450 patients with type 2 diabetes and hyperlipidemia, and the profiles of gut microbiota were analyzed using fecal samples in patients treated with metformin and a traditional Chinese herbal formula. An antidiabetic drug metformin (77) and herbal medicine significantly changed the gut microbiota profile that led to the enhancement of therapeutic effects of the drugs [110]. The traditional Chinese herbal formula used in the study contains the plants including Coptis chinensis, Momordica charantia, Rhizoma anemarrhenae, and Aloe vera, as well as red yeast rice from the fermentation; this herbal recipe is practically used in clinical application [110]. Among the plants used in this formula, Coptis chinensis contains an alkaloid berberine (78) (Figure 16). An independent study revealed that berberine (78) could significantly change the composition of gut microbiota in high-fat diet-fed rats [111]. An alkaloid berberine (78) was able to enrich selectively short-chain fatty acid-producing bacteria such as the genus Blautia and Allobaculum [111]. Another independent study also revealed that both metformin (77) and berberine (78) could change profiles of gut microbiota in high-fat diet-induced obesity in rats [112]. Substantial reduction of the diversity of gut microbiota was observed by both metformin (77) and berberine (78) because 60 out of the 134 operational taxonomic units were decreased after treatment with both drugs. However, there were considerable increases in short-chain fatty acid-producing bacteria, e.g., the genus Butyricicoccus, Blautia, Allobaculum, Phascolarctobacterium, and Bacteroides, after treatment with both metformin (77) and berberine (78) [112]. Therefore, in addition to the direct benefit toward the treatment of diabetes and obesity, the drugs, metformin (77) and berberine (78), could also improve gut microbiota profile by increasing short-chain fatty acid-producing bacteria and thus mediating their useful effects on the host [112]. As mentioned earlier in Section 2, gut microbiomes that produce short-chain fatty acids provide many beneficial effects on human health [24, 25].
Figure 16.
Structures of metformin (77), berberine (78), and theobromine (79).
Recent study revealed that berberine (78) could prevent ulcerative colitis by modifying gut microbiota and regulating T regulatory cell and T helper 17 cell in a dextran sulfate sodium-induced ulcerative colitis mouse model [113]. The diversity of gut microbiota was reduced by berberine (78), which markedly interfered the abundance of certain bacterial genus such as Bacteroides, Desulfovibrio, and Eubacterium. Therefore, the mechanisms of berberine (78) for the prevention of ulcerative colitis are by regulating the balance of T regulatory cell and T helper 17 cell, as well as by modifying gut microbiota [113]. Theobromine (79) (Figure 16) is a xanthine alkaloid of cocoa beans and found in chocolate, and its structure is closely related to caffeine. A cocoa-enriched diet containing theobromine (79) could decrease the intestinal immunoglobulin A secretion and immunoglobulin A-coating bacteria, i.e., the genus of Bacteroides, Staphylococcus, and Clostridium [114]. A cocoa-enriched diet had effects on a differential toll-like receptor pattern, which led to changes in the intestinal immune system [114]. Moreover, further experiments in rats revealed that a diet containing 10% cocoa and a diet supplemented with 0.25% theobromine (79) could reduce the gut bacterium Escherichia coli, while a diet with 0.25% theobromine (79) reduced the gut bacterial community of Clostridium histolyticum, C. perfringens, Streptococcus sp., and Bifidobacterium sp. [115]. The amounts of short-chain fatty acids increased after feeding rats with a diet containing 10% cocoa and that supplemented with 0.25% theobromine (79), while both diets decreased the abundance of immunoglobulin A (IgA)-coated bacteria. It is worth mentioning that gut IgA-coated bacteria could potentially cause intestinal disease such as inflammatory bowel disease, and eradication of these bacteria may prevent or reduce intestinal disease development [116]. Therefore, the active natural product theobromine (79) in cocoa able to reduce the amounts of immunoglobulin A-coated bacteria, and to modify the profile of gut microbiota, provides beneficial effects on human health [115].
It is known that berberine (78) has poor solubility; however, it can show effectiveness for the treatment of certain diseases; therefore, there might be a specific mechanism to deliver berberine (78) to an organ system. In an animal model, berberine (78) was found to convert to dihydroberberine (80) in an intestinal ecosystem of rats (Figure 17); the metabolite dihydroberberine (80) exhibited much better absorption rate than its parent drug, berberine (78) [117]. Incubation of berberine (78) with human gut bacteria isolated from gastrointestinal human specimens also produced dihydroberberine (80), and the amounts of dihydroberberine (80) obtained from the biotransformation of gut bacteria were higher than that obtained from other bacteria, which were not gut bacteria and used as the control. This experiment confirmed that gut microbiota could convert berberine (78) into its absorbable form, dihydroberberine (80); therefore intestinal microbiota is considered to be a “tissue” or an “organ” that is able to transform berberine (78) into an absorbable form, dihydroberberine (80) [117]. Mechanistic study revealed that gut microbiome uses the enzyme nitroreductases to catalyze the conversion of berberine (78) to dihydroberberine (80) (Figure 17). Dihydroberberine (80) was found to be absorbed in intestinal epithelia, but it was reverted to the active form berberine (78) soon after entering tissues of the intestinal wall. Detailed analysis showed that the conversion of dihydroberberine (80) back to berberine (78) was by a nonenzymatic oxidation through multi-faceted factors, for example, superoxide anion and metal ions, which occurred in intestinal epithelial tissues (Figure 17) [117]. Previous report demonstrated that dihydroberberine (80) in its sulfate form, e.g., dihydroberberine sulfate, also showed better absorption in the intestine than its parent drug, berberine (78) [118]. Recent independent studies revealed that dihydroberberine (80) has interesting biological activities, for example, anti-inflammatory activity through dual modulation of NF-κB and MAPK signaling pathways [119], synergistic effects with an anticancer drug sunitinib on human non-small cell lung cancer cell lines by inflammatory mediators and repressing MAP kinase pathways [120], and inhibition of ether-a-go-go-related gene (hERG) channels expressed in human embryonic kidney 293 (HEK293) cells [121]. It is worth mentioning that the metabolite products from gut biomicrobiota, i.e., dihydroberberine (80), have different biological activity from its parent drug, berberine (78). Therefore, the drug development process should include a research study on the metabolism of natural products (as drug candidates) by gut microbiota.
Figure 17.
Bioconversion of berberine (78) into an absorbable form, dihydroberberine (80), by gut bacteria; absorption of dihydroberberine (80) into the intestine wall and nonenzymatic conversion of dihydroberberine (80) to the active form berberine (78).
Demethyleneberberine (81), berberrubine (82), jatrorrhizine (83), and thalifendine (84) were found as major metabolites in rats after an oral administration of berberine (78) (Figure 18) [122]. Comparison of the levels of these metabolites in conventional rats (a control group) and pseudo germ-free rats revealed that liver and intestinal bacteria were involved in the metabolism and disposition of berberine (78) in vivo. It is worth mentioning that some metabolites from this biotransformation exert important biological activities. For example, demethyleneberberine (81) inhibits oxidative stress, steatosis, and mitochondrial dysfunction in a mouse model, which is a potential therapy for alcoholic liver disease [123]. Berberrubine (82) was found to reduce inflammation and mucosal lesions in dextran sodium sulfate-induced colitis in mice, which might be useful for the treatment of ulcerative colitis [124]. Jatrorrhizine (83) could reduce the uptake of 5-hydroxytryptamine and norepinephrine by the inhibition of uptake-2 transporters, thus exerting antidepressant-like action in mice [125]. Therefore, the biotransformation of berberine (78) by gut bacteria leads to the production of bioactive metabolites, which have interesting pharmacological properties; this underscores the impact of gut microbiota in the drug development process for natural products.
Figure 18.
Biotransformation of berberine (78) to demethyleneberberine (81), berberrubine (82), jatrorrhizine (83), and thalifendine (84) by gut bacteria.
Since there are interactions between gut microbiota and natural products, efforts have been made to use natural compounds for the treatment of gut microbiota dysbiosis, which is the imbalance of microorganisms in the human gastrointestinal tract. Dysbiosis of gut microbiota is strongly associated with some diseases such as type 2 diabetes, inflammatory bowel disease, obesity, and nonalcoholic fatty liver disease [16, 126]. Alkaloids of a medicinal plant, Corydalis saxicola, were used to prevent gut microbiota dysbiosis in an animal model [127]. Major alkaloids in Corydalis saxicola are berberine (78), jatrorrhizine (83), dehydrocavidine (85), palmatine (86), and chelerythrine (87) (Figures 18 and 19). Among these alkaloids, berberine (78), palmatine (86), and chelerythrine (87) are the main active principles for the treatment of antibiotic-induced gut microbiota dysbiosis through the key enzyme, CYP27A1, which is involved in the biosynthesis of bile acid [127]. This study provides insights for the discovery of natural products for the treatment of gut microbiota dysbiosis.
Figure 19.
Structures of dehydrocavidine (85), palmatine (86), and chelerythrine (87).
Xanthohumol (88) is a prenylflavonoid in hops (Humulus lupulus), which is responsible bitter flavor in beer (Figure 20). Xanthohumol (88) has interesting pharmacological properties, for example, improving cognitive flexibility in young mice [128] and having beneficial effects toward metabolic syndrome-related diseases such as type 2 diabetes and obesity [129]. The comparative study on germ-free and human microbiota-associated rats toward the metabolism of xanthohumol (88) revealed that gut bacteria could transform xanthohumol (88) to isoxanthohumol (89) and 8-prenylnaringenin (90), respectively (Figure 20) [130]. The metabolism of xanthohumol (88) was further studied using human intestinal bacteria, Eubacterium ramulus and E. limosum. It is worth mentioning that an independent study revealed that the bacteria of the genus Eubacterium are normally abundant in the human gastrointestinal tract; their densities in human gut are up to 1010 colony-forming units/g of intestinal content [131]. Xanthohumol (88) is spontaneously converted to isoxanthohumol (89), which is in turn bioconverted to 8-prenylnaringenin (90) by the gut bacterium, E. limosum (Figure 20) [132]. 8-Prenylnaringenin (90) is biotransformed to O-desmethylxanthohumol (91) by the bacterium E. ramulus; this bacterium could also convert O-desmethylxanthohumol (91) to desmethyl-α,β-dihydroxanthohumol (92). Moreover, the bacterium E. ramulus was able to transform xanthohumol (88) to α,β-dihydroxanthohumol (93) (Figure 20) [132]. An independent study in healthy women volunteers revealed that isoxanthohumol (89) could be bioconverted to 8-prenylnaringenin (90) in human intestine and that the bacterial microbiota isolated from fecal samples of female volunteers could also biotransform isoxanthohumol (89) to 8-prenylnaringenin (90) [133]. Another study demonstrated that 8-prenylnaringenin (90) has potent estrogenic property, and it could relieve climacteric symptoms, i.e., vasomotoric complaints and osteoporosis, and may be useful for the treatment of menopausal complaints [134]. These studies conclusively show that the metabolites produced by gut microbiome, i.e., 8-prenylnaringenin (90), are actually bioactive compounds, not the parent natural products, and they have different pharmacological activities from their parent natural products. Gut microbiome is therefore important for in vivo biotransformation of natural products, providing bioactive metabolites responsible for therapeutic effects.
Figure 20.
Bioconversion of xanthohumol (88) to isoxanthohumol (89), 8-prenylnaringenin (90), O-desmethylxanthohumol (91), desmethyl-α,β-dihydroxanthohumol (92), and α,β-dihydroxanthohumol (93) by human gut bacteria.
Gut microbiome can biotransform natural products to bioactive metabolite essentially for therapeutic effects, for example, the biotransformation of isoxanthohumol (89) to bioactive 8-prenylnaringenin (90) [133]. However, gut microbiome can also produce toxic metabolites from the biotransformation of natural products, thus giving negative side effects. Camptothecin (CPT) is a natural alkaloid of a plant, Camptotheca acuminata, and has anticancer property with topoisomerase inhibitory activity [135]. Irinotecan or CPT-11 (94) is an alkaloid derivative of camptothecin and used as anticancer drug (Figure 21). Irinotecan (94) is a prodrug, which is transformed in vivo through hydrolysis by carboxylesterase enzymes, giving an active metabolite, SN-38 (95) (Figure 21) [136]. Uridine diphosphate-glucuronosyltransferase enzymes catalyze the conversion of SN-38 (95) to a glucuronidated derivative, SN-38G (96) (Figure 21). The metabolite SN-38G (96) is inactive for cancer cells and is excreted into the gastrointestinal tract [137], where the gut bacteria use β-glucuronidase enzymes to convert SN-38G (96) to SN-38 (95) that causes severe diarrhea in patients (Figure 21) [138]. This side effect reflects the significant negative effects of gut bacteria in the drug metabolism. However, the use of antibiotics, e.g., levofloxacin, to reduce the population of gut bacteria in the gastrointestinal tract is not recommended for patients because it has many consequent problems [139]. Gut microbiotas are important for a healthy gastrointestinal tract, and they play many essential roles in dietary metabolisms [140, 141]; the treatment of cancer should not give any effects to gut microorganisms. Therefore, the use of antibiotic drugs, which affect gut microbiota, is not recommended. To reduce the diarrhea side effect without affecting gut microorganisms, a research led by Redinbo employed appropriate inhibitors of gut bacterial β-glucuronidase enzymes, in order to prevent the formation of SN-38 (95), a causative agent of severe diarrhea in patients [142]. Certain inhibitors exhibited β-glucuronidase inhibitory activity in living bacterial cells without disturbing the growth of gut bacteria or giving any damaging effects toward mammalian cells. Indeed, in a mouse model, mice treated with both irinotecan (94) and a β-glucuronidase inhibitor had less diarrhea and bloody diarrhea than the group receiving only the drug irinotecan (94). Therefore, the inhibition of microbial β-glucuronidases could prevent the production of toxic metabolite, SN-38 (95), during the treatment of anticancer drug, irinotecan (94) [142]. This is an example of a toxic drug metabolite produced by the activity of gut microbiome, and the manipulation of the enzyme activity of gut bacteria could be done by using another drug (an inhibitor of bacterial enzyme).
Figure 21.
Structures of irinotecan or CPT-11 (94) and its metabolites, SN-38 (95) and SN-38G (96), and the bioconversion of SN-38G (96) to SN-38 (95) by gut bacterial β-glucuronidase.
Some natural products can alter the composition of gut microbiome, and changes in gut microbiome lead to the drug-induced negative side effects on certain treatments. Paclitaxel or Taxol (97) is an anticancer drug for the treatment of many types of cancers (Figure 22), and it is a natural product isolated from a Pacific yew tree, Taxus brevifolia. In a mouse model, paclitaxel (97) chemotherapy could change the composition of gut bacterial community and induce negative effects such as sickness behaviors, i.e., fatigue and anorexia, increased central and peripheral inflammation, and impaired cognitive performance [143]. These negative effects might be associated with changes in gut bacteria because paclitaxel (97) therapy decreased the abundance of gut bacteria including Lachnospiraceae bacteria and butyrate-producing bacteria, which are necessary for human gut health [143]. Therefore, the negative effects of cancer chemotherapy may be attenuated by improving the composition of gut microbiota, for example, the use of prebiotic or probiotic supplements, which has become one of the emerging approaches to change the microbiota composition, thus improving therapeutic outcome for patients treated with anticancer drugs [144].
Figure 22.
Structure of an anticancer drug paclitaxel or Taxol (97).
Antibiotic drugs have significant effects on the metabolism of drugs and phytochemicals because they could suppress enzymatic activities of gut microbiome [92]. Therefore, if patients are treated with an antibiotic drug together with another drug, there are possible drug–drug interactions due to changes of gut microbiota caused by antibiotic drugs. Lovastatin (98) (Figure 23), a natural polyketide isolated from the fungus Aspergillus terreus [145], is a cholesterol-lowering drug, which is a member of the statin family. Lovastatin (98) has the interactions with antibiotics through the mediation of gut microbiome [146]. Incubation of lovastatin (98) with human and rat fecalase revealed the biotransformation of this drug by gut microbiota, giving four major metabolites including demethylbutyryl-lovastatin (99), hydroxylated-lovastatin (100), hydroxy acid-lovastatin (101), and OH-hydroxy acid-lovastatin (102) (Figure 23) [146]. These four metabolites were also found in rat plasma, and they might be from gut microbiota-mediated metabolism of the drug lovastatin (98). Among the drug metabolites, hydroxy acid-lovastatin (101) is the active form, which could effectively inhibit 3-hydroxy-3-methylglutaryl coenzyme-A reductase, the target enzyme of this cholesterol-lowering drug [147].
Figure 23.
Structures of major metabolites of lovastatin (98) including demethylbutyryl-lovastatin (99), hydroxylated-lovastatin (100), hydroxy acid-lovastatin (101), and OH-hydroxy acid-lovastatin (102).
In an animal model, rats with an oral administration of lovastatin (98) were compared with those treated with lovastatin (98) and antibiotics; the pharmacokinetic study revealed that the levels of the active metabolite hydroxy acid-lovastatin (101) in antibiotic-treated rats were lower than that without antibiotics. This result indicates that antibiotic drugs reduce the biotransformation of the drug lovastatin (98) to its active form, hydroxy acid-lovastatin (101), because antibiotics affect gut microbiome. The in vivo metabolism of lovastatin (98) to its active form, hydroxy acid-lovastatin (101), is important for the therapeutic efficacy of this drug; therefore antibiotic intake of patients treated with lovastatin (98) would lead to the decrease of the active form, hydroxy acid-lovastatin (101), thus decreasing its therapeutic effects [146]. This study clearly demonstrates the drug–drug interaction mediated by changes of gut microbiome.
4. Conclusions
Intriguingly, gut microbiome is very important for human health and diseases, and it is therefore recognized as an “organ” or a “tissue” in the human body. Gut microorganisms have much more genes encoding enzymes than those of human genome; therefore, enzymes of these microbes are involved in many biochemical processes, i.e., metabolism of xenobiotics (compounds not produced in human host, e.g., drugs and pollutants) and dietary sources. Metabolites produced by gut microbiome play significant roles in human health and diseases; these metabolites include short-chain fatty acids such as butyrate (11), as well as other metabolites, e.g., nicotinamide (12), 5-aminovaleric acid (14), and taurine (15) (see Section 2). Since gut microbiome and its metabolites substantially contribute to human health and diseases, a therapy by intervention strategies using gut microbiota can potentially be useful for some diseases, for example, metabolic disorders, cardiovascular disease, food allergy, and neurological disorders. Supplementation with probiotics or certain gut bacteria, as well as their metabolites, may be a new therapeutic method in the future. Fecal microbiota transplantation, e.g., transferring gut bacteria from healthy individuals into patients, is a challenging research study in the near future.
Gut microbiome can metabolite commonly used drugs and natural products. Drug metabolism by gut microorganisms decreases the levels of drugs in serum, thus disturbing the drug pharmacokinetics, which can lead to alteration of therapeutic efficiency. Moreover, metabolites produced by the drug metabolism of gut microbiome contribute considerably to the drug efficacy. For example, the levels of the drug L-dopa (56) are substantially reduced by the metabolic activity of gut microbiome, and this results in the requirement of higher doses for the Parkinson’s patients with gut microbiome that has high metabolic activity toward the drug L-dopa (56) (see Section 3.1). This example well demonstrates the role of gut microorganisms on treatment outcomes of the commonly used drugs. Gut microbiome could improve many drug therapies, for example, cancer immunotherapy targeting CTLA-4 blockade and immune checkpoint inhibitor via the PD-1/PD-L1 pathway. Moreover, the metabolism of gut microbiome improves drug efficacy because it assists the bioconversion of some drugs into their active forms, for example, a biotransformation of lovastatin (98) to its active form, hydroxy acid-lovastatin (101), and a bioconversion of aspirin (70) to salicylic acid (71) that actively reduces pain. Interestingly, gut microbiome involves in a biotransformation of an alkaloid natural product berberine (78) to an absorbable form, dihydroberberine (80), which is absorbed at the intestine system (see Section 3.2). This result demonstrates that gut microbiome facilitates drug delivery of berberine (78) that has poor solubility by a biotransformation to an absorbable form, dihydroberberine (80), which is in turn converted to its active form berberine (78) in the human body. Since gut microbiome plays many important roles in drugs and natural products, the metabolism of natural products and drug candidates by gut microbiome should therefore be studied, and it should be a part of the drug development process. Gut microbiome can potentially play a crucial role for the improvement of drug safety and efficacy.
Acknowledgments
The author thanks the Center of Excellence on Environmental Health and Toxicology, Science & Technology Postgraduate Education and Research Development Office (PERDO), Ministry of Education, for the support of research that leads to this book chapter.
Conflict of interest
The author declares no competing interests or no conflict of interest.
\n',keywords:"gut microbiota, gut microbiome, drug-microbiome interactions, drug-microbiota interactions, natural products-microbiome interactions, drug metabolism, drug toxicity, biotransformation, bioconversion",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/72563.pdf",chapterXML:"https://mts.intechopen.com/source/xml/72563.xml",downloadPdfUrl:"/chapter/pdf-download/72563",previewPdfUrl:"/chapter/pdf-preview/72563",totalDownloads:71,totalViews:0,totalCrossrefCites:0,dateSubmitted:"February 26th 2020",dateReviewed:"May 15th 2020",datePrePublished:"June 19th 2020",datePublished:null,dateFinished:null,readingETA:"0",abstract:"Trillions of microorganisms with a complex and diverse community are in the human gastrointestinal tract. Gut microbial genomes have much more genes than human genome, thus having a variety of enzymes for many metabolic activities; therefore, gut microbiota is recognized as an “organ” that has essential functions to human health. There are interactions between host and gut microbiome, and there are correlations between gut microbiome in the healthy state and in certain disease states, such as cancer, liver diseases, diabetes, and obesity. Gut microbiota can produce metabolites from nutrients of dietary sources and from drug metabolisms; these metabolites, for example, short-chain fatty acids (SCFAs), have substantial effects on human health. Drug-microbiome interactions play a crucial role in therapeutic efficiency. Some drugs are able to change compositions of gut microbiota, which can lead to either enhance or reduce therapeutic efficiency. This chapter provides an overview of roles of gut microbiota in human health and diseases and recent research studies on the metabolism or toxicity of drugs and natural products. Since gut bacteria considerably contribute to drug metabolism, research on the influence of gut microbiome on drug candidates (or natural products) should be part of the drug development processes.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/72563",risUrl:"/chapter/ris/72563",signatures:"Prasat Kittakoop",book:{id:"9403",title:"Human Microbiome",subtitle:null,fullTitle:"Human Microbiome",slug:null,publishedDate:null,bookSignature:"Prof. Natalia Beloborodova and Prof. A.V. Grechko",coverURL:"https://cdn.intechopen.com/books/images_new/9403.jpg",licenceType:"CC BY 3.0",editedByType:null,editors:[{id:"199461",title:"Prof.",name:"Natalia",middleName:null,surname:"Beloborodova",slug:"natalia-beloborodova",fullName:"Natalia Beloborodova"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:null,sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Contributions of metabolites produced by gut microbiome to human health and diseases",level:"1"},{id:"sec_3",title:"3. Interactions of gut microbiome and drugs and/or natural products",level:"1"},{id:"sec_3_2",title:"3.1 Interactions of gut microbiome and commonly used drugs",level:"2"},{id:"sec_4_2",title:"3.2 Interactions of gut microbiome and natural products",level:"2"},{id:"sec_6",title:"4. Conclusions",level:"1"},{id:"sec_7",title:"Acknowledgments",level:"1"},{id:"sec_10",title:"Conflict of interest",level:"1"}],chapterReferences:[{id:"B1",body:'Sanders ME, Merenstein DJ, Reid G, Gibson GR, Rastall RA. Probiotics and prebiotics in intestinal health and disease: From biology to the clinic. Nature Reviews. Gastroenterology & Hepatology. 2019;16(10):605-616. DOI: 10.1038/s41575-019-0173-3'},{id:"B2",body:'Matthies A, Loh G, Blaut M, Braune A. Daidzein and genistein are converted to equol and 5-hydroxy-equol by human intestinal Slackia isoflavoniconvertens in gnotobiotic rats. 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Chulabhorn Graduate Institute, Program in Chemical Sciences, Chulabhorn Royal Academy, Thailand
Chulabhorn Research Institute, Thailand
Center of Excellence on Environmental Health and Toxicology (EHT), CHE, Ministry of Education, Thailand
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The study was implemented by conducting a series of METRIC applications for two Landsat WRS path overlap areas, one in southern Idaho (paths 39 and 40) during 2000, and a second one in Nebraska (paths 29 and 30) during 2002, years when two fully functioning satellites, Landsat 5 and Landsat 7, were in orbit. The results indicated that high frequency imagery provided by two satellites covering a WRS path overlap was more able to capture the impacts of rapid crop development and harvest, and evaporation associated by wetting events. That data set simulated a nominal four-day revisit time. Three-simulated 16-day revisit data sets created using a single Landsat series for a single path were unable to produce monthly and growing season ET due to the lack of sufficient number of images to even begin the time-integration process. This emphasizes the need to maintain two Landsat satellites in orbit and the high value of four-day revisit times. Limiting the data set to one path and two satellites (eight-day revisit) underestimated growing season ET accordingly by about 8% on average. Error in monthly ET was relatively high when image availability was limited to that for an eight-day revisit. This is due to the importance of timing of images to identify key inflection points in the ETrF curves and to capture special events such as wetting events from irrigation and rain or from water stress or cuttings, as in the case of forage crops. Results suggest that a four-day revisit time as represented by the full-run (run 1) of our analysis provides robustness in the development of time-integrated ET estimates over months and growing seasons, and is a valuable backstop for mitigation of clouded images over extended periods.",signatures:"Ricardo Trezza, Richard G. 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Over the years he received several awards, including “Young Scientist Award-2018” by Royal Association of Science-led Socio-Cultural Advancement at national seminar on “Smart technologies to boost farm productivity and socio-economic status of rural India” organized by Sher-e- Kashmir University of Agricultural Sciences and Technology of Jammu, Chatha (SKUAST) during 19-20 November 2018. Dr. Bhat has authored and co-authored more than 60 research articles and 10 book chapters.",institutionString:"Regional Research Station",institution:null},{id:"271319",title:"Dr.",name:"Masahiro",surname:"Tasumi",slug:"masahiro-tasumi",fullName:"Masahiro Tasumi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null}]},generic:{page:{slug:"open-access-funding-funders-list",title:"List of Funders by Country",intro:"
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UK Research and Innovation (former Research Councils UK (RCUK) - including AHRC, BBSRC, ESRC, EPSRC, MRC, NERC, STFC.) Processing charges for books/book chapters can be covered through RCUK block grants which are allocated to most universities in the UK, which then handle the OA publication funding requests. It is at the discretion of the university whether it will approve the request.)
UK Research and Innovation (former Research Councils UK (RCUK) - including AHRC, BBSRC, ESRC, EPSRC, MRC, NERC, STFC.) Processing charges for books/book chapters can be covered through RCUK block grants which are allocated to most universities in the UK, which then handle the OA publication funding requests. It is at the discretion of the university whether it will approve the request.)
Wellcome Trust (Funding available only to Wellcome-funded researchers/grantees)
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