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These books synthesize perspectives of renowned scientists from the world’s most prestigious institutions - from Fukushima Renewable Energy Institute in Japan to Stanford University in the United States, including Columbia University (US), University of Sidney (AU), University of Miami (USA), Cardiff University (UK), and many others.
\\n\\nThis collaboration embodied the true essence of Open Access by simplifying the approach to OA publishing for Academic editors and authors who contributed their research and allowed the new research to be made available free and open to anyone anywhere in the world.
\\n\\nTo celebrate the 50 books published, we have gathered them at one location - just one click away, so that you can easily browse the subjects of your interest, download the content directly, share it or read online.
\\n\\n\\n\\n\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'
IntechOpen and Knowledge Unlatched formed a partnership to support researchers working in engineering sciences by enabling an easier approach to publishing Open Access content. Using the Knowledge Unlatched crowdfunding model to raise the publishing costs through libraries around the world, Open Access Publishing Fee (OAPF) was not required from the authors.
\n\nInitially, the partnership supported engineering research, but it soon grew to include physical and life sciences, attracting more researchers to the advantages of Open Access publishing.
\n\n\n\nThese books synthesize perspectives of renowned scientists from the world’s most prestigious institutions - from Fukushima Renewable Energy Institute in Japan to Stanford University in the United States, including Columbia University (US), University of Sidney (AU), University of Miami (USA), Cardiff University (UK), and many others.
\n\nThis collaboration embodied the true essence of Open Access by simplifying the approach to OA publishing for Academic editors and authors who contributed their research and allowed the new research to be made available free and open to anyone anywhere in the world.
\n\nTo celebrate the 50 books published, we have gathered them at one location - just one click away, so that you can easily browse the subjects of your interest, download the content directly, share it or read online.
\n\n\n\n\n'}],latestNews:[{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"}]},book:{item:{type:"book",id:"2509",leadTitle:null,fullTitle:"Recent Advances in Novel Drug Carrier Systems",title:"Recent Advances in Novel Drug Carrier Systems",subtitle:null,reviewType:"peer-reviewed",abstract:"This contribution book collects reviews and original articles from eminent experts working in the interdisciplinary arena of novel drug delivery systems and their uses. 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\r\n\tThe book Trichoderma aims to assist in the integrated management of plant diseases with applications in all cultivation systems (including vegetables, cereals, oilseeds and fruit trees). Parasitism, identification of species, ultrastructure and molecular aspects (uses of SSR and snips techniques) of the interaction of the biocontrol agent and the seeds, roots and the phyllosphere will also be discussed, taking into account all the modalities of use of this important and versatile microorganism. Aspects of its application involving products and their formulations for use by farmers, as well as management tactics involving other biocontrol agents such as bacteria, use of organic matter, vegetation cover and resistant or tolerant varieties for some pathosystem will also be addressed.
\r\n\r\n\tThe book will discuss integrated management of plant diseases and plant protection, with an emphasis on phytopathogenic fungi, biocontrol, plant genetics and resistance.
",isbn:"978-1-80355-355-9",printIsbn:"978-1-80355-354-2",pdfIsbn:"978-1-80355-356-6",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,isSalesforceBook:!1,isNomenclature:!1,hash:"adeba4522858a6406df7ad737a4f1956",bookSignature:"Dr. Fernando Cezar Cezar Juliatti",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11317.jpg",keywords:"Mechanisms of Trichoderma Species, Morphology, Identification, Molecular Techniques, Uses and Field Application, Bioprospecting, Systemic Acquired Resistance (SAR), Resistance, Fungicides, Integrated Pest Management (IPM), Biocontrol, Application Modes",numberOfDownloads:292,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfDimensionsCitations:0,numberOfTotalCitations:0,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"September 3rd 2021",dateEndSecondStepPublish:"October 1st 2021",dateEndThirdStepPublish:"November 30th 2021",dateEndFourthStepPublish:"February 18th 2022",dateEndFifthStepPublish:"April 19th 2022",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"9 months",secondStepPassed:!0,areRegistrationsClosed:!0,currentStepOfPublishingProcess:5,editedByType:null,kuFlag:!1,biosketch:"Dr. Juliatti is the Professor and Researcher at the Federal University of Uberlândia and President of the Brazilian Association of Agriculture Education. 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From 1998 to 2000, he presided over the implementation of the Graduate Program in Agronomy at Federal University of Uberlândia (master's and doctorate). He was director of the Institute of Agricultural Sciences at Federal University of Uberlândia from 2001 to 2004. He was president of the Brazilian Society of Phytopathology in the period from 2003 till 2004. Dr Juliatti is a member of the Brazilian Societies of Phytopathology, Plant Breeding and Brazilian Horticulture in addition to the Paulista Group of Phytopathology. He is technical consultant in the areas of corn and soybeans/ phytopathological problems in the Brazilian savannah. \nHe and the Plant Improvement team at Federal University of Uberlândia developed strains of soybean, tomato and beans with multiple resistance to phytopathogens. Together with this team, he launched 05 protected soybean cultivars for the Brazilian savannah with multiple resistance to important soybean pathosystems, including partial resistance to Soybean Asian rust. \nHe chaired the organizing committee of the Brazilian Congress on Agroenergy and the First International Symposium on Biofuel. He coordinated the Chamber of Agronomy of CREA-MG (in 2008 and 2009) and the National Coordination of Agronomy of the CREA / CONFEA system (in 2009). He is a coordinator of the Latin American Committee on studies on Sclerotinia (Sclerotinia International Working Group). Dr Juliatti is a Financial Director of SMEA (Minas Gerais Society´ of the Agronomy Engineers) and current member of the Fiscal Council of the same entity. He is also President of ABEAS (Brazilian Association of Higher Agricultural Education - Triennium 2011-2013 and 2013-2016). He is Winner of the 2011 Top Ethanol Award in the area of technological innovation in industrial energy offered by UNICA and Winner in 2008 and 2013 of the Top Science Award offered by the company Basf. S.A.\nDr Juliatti is a permanent professor in the Graduate Programs in Agronomy (UFU, Brazil - Master and Doctorate) and Biofuels (UFU-UFVJM - Master and Doctorate). He was the Technical Director for four terms at the Association of Agricultural Engineers of Triângulo Mineiro and Alto Paranaíba, Minas Gerais, Brazil. He was President of the Triângulo Mineiro and Alto Paranaíba Association (AGROTAP), from 2017 to 2018 . In 2017 he was President of 50 Brazilian Congress of Phytopathology (Golden Jubilee) and 16 International Workshop on Sclerotinia and II Brazilian Workshop on Soybean Rust. Currently he is coordinator of the UFU Agronomy Course at the Campus Uberlândia. He published more 200 articles in important journals from Brazil and other countries, 11 books and 12 chapters in the field of Agronomy.",institutionString:"Federal University of Uberlândia",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"4",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Federal University of Uberlândia",institutionURL:null,country:{name:"Brazil"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"13",title:"Immunology and Microbiology",slug:"immunology-and-microbiology"}],chapters:[{id:"80375",title:"Trichoderma: A Biofertilizer and a Bio-Fungicide for Sustainable Crop Production",slug:"trichoderma-a-biofertilizer-and-a-bio-fungicide-for-sustainable-crop-production",totalDownloads:131,totalCrossrefCites:0,authors:[null]},{id:"81107",title:"Can Genus Trichoderma Manage Plant Diseases under Organic Agriculture?",slug:"can-genus-trichoderma-manage-plant-diseases-under-organic-agriculture",totalDownloads:85,totalCrossrefCites:0,authors:[null]},{id:"80357",title:"Trchoderma Spp.: Their Impact in Crops Diseases Management",slug:"trchoderma-spp-their-impact-in-crops-diseases-management",totalDownloads:77,totalCrossrefCites:0,authors:[null]}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"418641",firstName:"Iva",lastName:"Ribic",middleName:null,title:"M.Sc.",imageUrl:"https://mts.intechopen.com/storage/users/418641/images/16830_n.png",email:"iva.r@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. 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For example, there are applications in propagation of beams and waves, the generation of diffusion profiles and diffraction patterns, imaging and tomographic reconstructions, designs of beams, boundary value problems, etc. The Hankel transform also has a natural relationship to the Fourier transform since the Hankel transform of zeroth order is a 2D Fourier transform of a rotationally symmetric function. Furthermore, the Hankel transform also appears naturally in defining the 2D Fourier transform in polar coordinates and the spherical Hankel transform also appears in the definition of the 3D Fourier transform in spherical polar coordinates [1, 2].
\nAs useful as the Hankel transform may be, there is no discrete Hankel transform (DHT) that exists that has the same relationship to the continuous Hankel transform in the same way that the discrete Fourier transform (DFT) exists alongside the continuous Fourier transform. By this, we mean that the discrete transform exists as a transform in its own right, has its own mathematical theory of the manipulated quantities, and finally as an added bonus, can be used to approximate the continuous version of the transform, with relevant sampling and interpolation theories. Until recently, a discrete Hankel transform merely implied an attempt to discretize the integral(s) of the continuous Hankel transform, rather than an independent discrete transform in its own right.
\nSuch a theory of a DHT was recently proposed [3]. Thus, goal of this chapter is to outline the mathematical theory for the DHT. The mathematical standard set of “DFT-like” rules of shift, modulation, multiplication and convolution rules are derived and presented. A Parseval-like theorem is presented, as are sampling and interpolation theorems. The manner in which this DHT can be used to approximate the continuous Hankel transform is also explained.
\nTo start, we define the Hankel transform and Fourier-Bessel series as used in this work.
\nThe
where \n
Thus, Hankel transforms take functions in the spatial
It is known that functions defined on a finite portion of the real line \n
where the order,
Eqs. (3) and (4) can be considered to be a transform pair where the continuous function \n
Sampling and interpolation theorems supply the answers to some important questions. For example, given a bandlimited function in frequency space, a sampling theorem answers the question of which samples of the original function are required in order to determine the function completely. The interpolation theorem shows how to interpolate those samples to recover the original function completely. Here, a band-limit means boundedness in frequency. In many applications such as tomography, the notion of a band-limit is not necessarily a property of a function, but rather a limitation of the measurement equipment used to acquire measurements. These measurements are then used to reconstruct some desired function. Thus, the sampling theorem can also answer the question of how band-limits (frequency sensitivities) of measurement equipment determine the resolution of those measurements.
\nGiven a space-limited function, the sampling theorem answers the question of which samples in frequency space determine the function completely, i.e., those that are required to reconstruct the original function. In other words, the sampling theorem dictates which frequency measurements need to be made. As before, the interpolation theorem will give a formula for interpolating those samples to reconstruct the continuous function completely.
\nWe state here the sampling theorem in the same way that Shannon stated it for functions in time and frequency: if a spatial function \n
where the Fourier Bessel coefficients can be found from Eq. (4) as
\nIn (6), we have used the fact that \n
Hence, a function bandlimited to \n
Eq. (7) states that the samples \n
To verify that this sampling theorem is consistent with expectations, we recognize that the zeros of \n
It follows from Eq. (7) that \n
From Watson ([7], p. 134), we have the following result
\nEq. (9) can be used to simplify (8) to give
\nEq. (10) gives the formula for interpolating the samples \n
Eq. (8) states
\nIn other research work [8], the generalized shift operator \n
With this definition of a generalized shift operator, we recognize the integral in Eq. (12) as the inverse Hankel transform of the Boxcar function shifted by \n
where
\nThe boxcar function is a generalized version of the standard Rect function. The Rect function is usually defined as the function which has value 1 over the interval \n
For the relatively simple case of the zeroth-order Hankel transform, the inverse Hankel transform of the Boxcar function is given by
\nThe function \n
In fact, from Eqs. (13), (14) and (16), it follows that the generalized shifted version of the jinc function is given by
\nHence, for a zeroth-order Fourier Bessel transform, Eq. (12), the expansion for \n
Eq. (18) says that the interpolating function is a shifted jinc function, in analogy with a scaled sinc being the interpolating function for the sampling theorem used for Fourier transforms.
\nNow consider a space-limited function \n
where the Fourier Bessel coefficients can be found from
\nHere, we have used the definition of the Hankel transform \n
From Eq. (21), it is evident that the samples \n
The Hankel transform of the function can then be found from a forward Hankel transformation as
\nUsing Eq. (9), Eq. (22) can be simplified to give
\nEq. (23) gives the formula for interpolating the samples \n
Based on the sampling theorems above, in this section we explore how assuming that a function can be simultaneously band-limited and space-limited will naturally lead to a discrete Hankel transform. Although it is known that it is not possible to fulfill both of these conditions exactly, it
We demonstrated above that a band-limited function, with \n
Evaluating the previous Eq. (24) at the sampling points \n
For \n
Now, suppose that in addition to being band-limited, the function is also effectively space limited. As mentioned above, it is known that a function cannot be finite in both space and spatial frequency (equivalently it cannot be finite in both time and frequency if using the Fourier transform). However, if a function is
Hence, using the argument of “effectively space limited” in the preceding paragraph, we can terminate the series in Eq. (25) at a suitably chosen \n
In this case, the truncated sum in Eq. (26) does not represent \n
Concomitantly, we know that for any space-limited function then for \n
More specifically, suppose that we follow the logic from the previous section that the function \n
where we truncated the series in Eq. (28) at
Compare Eq. (29) to the “forward” transform from Eq. (26), repeated here for convenience, where we found that for \n
Eqs. (29) and (30) are the fundamental relations used for the discrete Hankel transform proposed in the following sections.
\nThe preceding development shows that a “natural,”
The relationship \n
It is pointed out in [10] that the zeros of \n
Eq. (32) becomes a better approximation to \n
Using this approximation, then \n
For larger values of
This is exactly analogous to the corresponding expression for Fourier transforms. Specifically, for temporal Fourier transforms Shannon [6] argued that “If the function is limited to the time interval
The preceding sections show that both forward and inverse discrete versions of the transforms contain an expression of the form
\nThis leads to a natural choice of kernel for the discrete transform, as shall be outlined in the next section. To aid in in the choice of kernel for the discrete transform, we present a useful discrete orthogonality relationship shown in [11] that for \n
where \n
If written in matrix notation, then the Kronecker delta of Eq. (38) is the identity matrix.
\nFisk-Johnson discusses the analytical derivation of Eq. (37) in the appendix of [11]. Eq. (37) is exactly true in the limit as \n
With inspiration from the notation in [11], and an additional scaling factor of \n
In Eq. (39), the superscripts
Furthermore, the orthogonality relationship, Eq. (37), states that
\nEq. (40) states that the rows and columns of the matrix \n
where \n
Similarly, the inverse transform, Eq. (29), can be written as
\nFollowing the notation in [12], we can also define a different \n
In Eq. (44), the superscripts
The orthogonality relationship, Eq. (37), can be written as
\nEq. (40) states that the rows and columns of the matrix \n
Therefore, the \n
Using the symmetric, orthogonal transformation matrix \n
Similarly, the inverse discrete transform of Eq. (29) can be written as
\nFrom the previous section is it clear that the two natural choices of kernel for a DHT are either \n
Here, the transform is of
where \n
The inverse discrete Hankel transform (IDHT) is then given by
\nThis can also be written in matrix form as
\nWe note that the forward and inverse transforms are the same.
\nWe show the proof for the \n
Switching the order of the summation in Eq. (54) gives
\nThe inside summations as indicated in Eq. (55) are recognized as yielding the Dirac-delta function, the orthogonality property of Eq. (40) (or Eq. (46) if using \n
Inner products are preserved and thus energies are preserved under the \n
The \n
However, under the \n
Making use of the now-present Dirac-delta function, Eq. (58) simplifies to give a modified Parseval relationship
\nIn other words, under a DHT using the \n
As a consequence of the orthogonality property of \n
where the overbar indicates a conjugate transpose and the superscript
For the formulation with \n
It is obvious from Eq. (59) that if we define the “scaled” vector
\nthen by straighforward substitution of scaled vectors and their conjugates, it follows that
\nIn keeping with the development of the well-known discrete Fourier transform, we develop the standard toolkit of rules for the discrete Hankel transform. In the following, \n
The discrete counterpart of the Dirac-delta function is the Kronecker-delta function, \n
The symbol \n
Here, \n
From Eq. (65), we can deduce the vector \n
As before, \n
where we have used the orthogonality relationship (40). This gives us another DHT pair:
\nFor a one-dimensional Fourier transform, one of the known transform rules is the shift rule, which states that
\nIn Eq. (69), \n
where \n
The shifted function \n
Changing the order of summation gives
\nAs indicated in Eq. (72), the quantity in brackets can be considered to be a type of shift operator acting on the original unshifted function. We can define this as
\nIt then follows that Eq. (72) can be written as
\nThis triple-product shift operator is similar to previous definitions of shift operators for multidimensional Fourier transforms that rely on Hankel transforms [1, 2] and of generalized Hankel convolutions [14, 15, 16].
\nWe now consider the forward DHT transform of the shifted function \n
Changing the order of summation gives
\nThis yields another transform pair and is the shift-modulation rule. This rule analogous to the shift-modulation rule for regular Fourier transforms whereby a shift in the spatial domain is equivalent to modulation in the frequency domain:
\nNote that Eq. (77) does
We consider the forward DHT of a function “modulated” in the space domain \n
and write \n
Then Eq. (78) becomes
\nInterchanging the order of summation gives
\nBy comparing Eq. (81) with Eqs. (72) and (73), we recognize the shift operator as indicated in (81). This produces a modulation-shift rule as would be expected so that the forward DHT of a modulated function is equivalent to a generalized shift in the frequency domain. This yields another transform pair:
\nIn other words, Eq. (82) says that modulation in the space domain is equivalent to shift in the frequency domain, as would be expected for a (generalized) Fourier transform.
\nWe consider the convolution using the generalized shifted function previously defined. The convolution of two functions is defined as
\nThe meaning of Eq. (83) follows from the traditional definition of a convolution: multiply one of the functions by a shifted version of a second function and then sum over all possible shifts.
\nSubsequently, from the definition of the inverse transforms, we obtain
\nBut from the orthogonality relationship (40), the summation over \n
The right hand side of Eq. (85) is clearly the inverse transform of the product of the transforms \n
It follows from Eq. (85) that interchanging the roles of \n
Therefore, it follows that
\nWe now consider the forward transform of a product in the space domain \n
Rearranging gives
\nThis gives us yet another transform pair that says that multiplication in the spatial domain is equivalent to convolution in the transform domain:
\nInterchanging the roles of \n
Eqs. (26) and (29) show how the DHT can be used to calculate the continuous Hankel transform at finite points. From Eqs. (26) and (29), it is clear that given a continuous function \n
where \n
Similarly, given a continuous function \n
For both the forward and inverse transforms, \n
The relationship \n
In order to properly use the discrete transform to approximate the continuous transform, a function has to be sampled at specific discretization points. For a finite spatial range \n
It is important to note that as in the case of the computation of the transformation matrix \n
The software used to calculate the DHT is based on the MATLAB programming language. The software can be downloaded from
The implementation of the discrete Hankel transform is decomposed into distinct functions. These functions consist of various steps that have to be performed in order to properly execute the transform. These steps are as follows:
Calculate \n
Generate of \n
Sample the function (if needed)
Create the \n
Perform the matrix-function multiplication
The steps are the same regardless if the function is in the space or frequency domain. Furthermore, the \n
Function name | \nCalling sequence | \nDescription | \n
---|---|---|
besselzero | \nbesselzero(n,k,kind) | \nCalculation of | \n
freqSampler | \nfreqSampler(R,zeros) | \nCreation of sample points in the frequency domain (Eq. (95)) | \n
spaceSampler | \nspaceSampler(R,zeros) | \nCreation of sample points in the space domain (Eq. (95)) | \n
YmatrixAssembly | \nYmatrixAssembly(n,N,zeros) | \nCreation of \n | \n
Set of available functions.
Additionally, the matlab script
The software was tested by using the DHT to approximate the computation of both the continuous Hankel forward and inverse transforms and comparing the results with known (continuous) forward and inverse Hankel transform pairs. Different transform orders \n
For the purpose of testing the accuracy of the DHT and IDHT, the dynamic error was used, defined as [12]
\nThis error function compares the difference between the exact function values \n
In this chapter, the theory of the discrete Hankel transform as a “standalone” transform was motivated and presented. The standard operating rules for multiplication, modulation, shift and convolution were also demonstrated. Sampling and interpolation theorems were shown. The theory and numerical steps to use the presented discrete theory for the purpose of approximating the continuous Hankel transform was also shown. Links to the publicly available, open-source numerical code were also included.
\nThe author acknowledges the contributions of Mr. Ugo Chouinard, who developed and tested the numerical code to which links are provided in this chapter. This work was financially supported by the Natural Sciences and Engineering Research Council of Canada.
\nThe author declares that there are no conflicting interests.
Bioprocesses, which are consisted of a series of enzymatically catalyzed biochemical reactions in all living things, are necessary for survival. They have a high potential in terms of material synthesis, which has recently been performed by chemical techniques [1]. Furthermore, the advancement of heterologous production systems and genetic engineering techniques has resulted in pioneering initiatives to manufacture usable biomaterials [2]. These advancements also enabled the successful generation of primary and secondary metabolic pathway products in physiologically and genetically well-defined hosts, such as
NRPs are secondary metabolites that are synthesized outside of the ribosomal machinery and have a variety of properties such as cytostatics, immunosuppressants or anticancer agents, antibiotics, pigments, siderophores, toxins [3, 5, 6]. NRPs are typically produced by marine microorganisms and invertebrates, as well as soil-inhabiting microorganisms [5, 7, 8]. The majority of natural products produced by sponges, bryozoans, mollusks, and tunicates are members of the NRP or mixed polyketide–NRP families. Several of NRPs are being used in the development of new medicines for inflammatory, cancer, neurological diseases, and infectious disease nowadays [7].
Non-ribosomal peptide synthetases (NRPSs) enzymes are poly-functional mega-synthases that biosynthesize NRPs [7, 9, 10]. NRPSs, multi-modular enzyme or enzyme complexes from common bacteria, less common eukarya, and rare archaea, are capable of producing a wide range of natural pharmaceutical products (Bacitracin, antibiotics for skin infections; Bleomycin antitumor; Cyclosporin, antifungal, and immunosuppressive drugs; Daptomycin, antibiotics) [5, 7, 11]. NRPSs use both proteinogenic and nonproteinogenic amino acids (not encoded by DNA) as building blocks for the growing peptide chain [1, 7, 11, 12]. They catalyze multiple biosynthetic processes, each of which is responsible for particular one amino acid elongation on the growing peptide chain [10]. This chapter looks at the structure, function, and synthesis of NRPs, as well as producer microorganisms and their various applications.
NRPSs are responsible for nonribosomal peptide (NRP) synthesis. These are large multi-enzyme complexes that are modularly organized and serve as biosynthetic machinery and templates [5, 11, 12, 13, 14]. For example, a single NRPS of 1.6 MDa synthesizes the Cyclosporine A (7). In fungal systems, such as in the case of cyclosporine A (7), a single NRPS synthesizes peptides, whereas bacteria frequently use numerous NRPSs with genes grouped in an operon. NRPSs have a modular structure [14, 15].
In a genome mining research of 2699 genomes, Wang et al. found that more than half of the NRPS enzymes were non-modular NRPS enzymes [16]. Nonmodular NRPS enzymes can be found in siderophore biosynthesis pathways, such as EntE and VibH in enterobactin and VibE in vibriobactin, or as a standalone peptidyl carrier protein, such as BlmI from the bleomycin gene cluster. NRPS enzymes are found frequently in bacteria, less frequently in eukaryotes, and infrequently in archaea. Actinobacteria, Cyanobacteria, Firmicutes, and Proteobacteria were the phyla with the greatest number of these enzymes in the bacterial domain. There was a correlation between genome size and the number of NRPS clusters [5, 17].
A module is a part of the NRPS polypeptide chain that is in charge of integrating one amino acid into the final product. Modules can further be separated into domains (Figure 1), which represent enzyme units that catalyze distinct steps of NRP synthesis. On the protein level, domains are defined by distinctive, greatly conserved order of patterns known as “core motifs.” In certain instances, biochemical and structural data were used to confirm the involvement of greatly conserved residues in domain function (Table 1) [14].
Catalyzed reactions by various NRPS-domains [
A1 L(TS)YxEL A2 LKAGxAYL(VL)P(LI)D A3 LAYxxYTSG(ST)TGxPKG A4 FDxS A5 NxYGPTE A6 GELxJGx(VL)ARGYL A7 Y(RK)TGDL A8 GRxPxQVKIRGxRIELGEIE A9 LPxYM(IV)P A10 NGK(VL)DR | T LGG(DH)SL |
C1 SxAQxR(LM)(WY)xL C2 RHExLRTxF C3 MHHxISDG(WV)S C4 YxD(FY)AVW C5 (IV)GxFVNT(QL)(CA)xR C6 HN)QD(YD)PFE C7 RDxSRNPL | Te GxSxG |
E1 PIQxWF E2 HHxISDG(WV)S E3 DxLLxAxG E4 EGHGRE E5 RTVGWFTxxYP(YV)PFE E6 PxxGxGYG E7 FNYLG(QR) | Cy1 FPL(TS)xxQxAYxxGR Cy2 RHx(IM)L(PAL)x(ND)GxQ C3 D(NLI)xDxxS Cy3 LPxxPxLPLxxxP Cy4 (TS)(PA)3x(LAF)6x(IVT)LxxW Cy5 (GA)DFTxLxLL Cy6 PVVFTSxL Cy7 (ST)(QR)TPQVx(LI)D13xWD |
Ox1 KYxYxSxGxxY(PG)VQ Ox2 GxxxG(LV)xxGxYYY(HD)P Ox3 IxxxYG | M1 VL(DE)xGxGxG M2 NELSxYRYxAV M3 VExSxARQxGxLD |
R1 V(L)(L)TG(A)TG(F)(L)GxxLL R2 Vx(L)(L)VR(A) R3 GPL(G)x(P)x(L)GL R4 V(Y)PYxYLxx(P)NVxxT R5 GYxxSKW(A)(A)E R6 R(P)G R7 YxxxxG(LF)LxxP |
NPRS-domains’ core-motifs [14].
There are three domains in a module. These are 1) the adenylation (A) domain, 2) the peptidyl carrier protein (PCP) or thiolation (T) domain, and 3) the condensation (C) domain, all of which are responsible for the synthesis of NRPs. A module may include additional tailoring or altering domains incorporating epimerization (E), methylation and oxidation domains or a heterocyclization (Cy) domain in place of a C-domain. Finally, most NRPS termination modules have a TE-domain, which is in charge of releasing linear, cyclic, or branching cyclic peptides [5, 9, 10, 11, 15, 18, 19, 20, 21].
The order of the modules is frequently aligned with the sequences of the resulting peptides. NRP synthesis begins at the N-terminus and ends at the C-terminus, yielding peptides that are typically 3–15 amino acids long. The released peptides contain amino acids, that is, imino acids or ornithine and their structures are linear, cyclic-macrocyclic, branched-cyclic, branched-macrocyclic, dimers or trimers of identical structural elements [5].
The A-domain is responsible for the first step in biosynthesis, which involves recognizing and activating the amino acid substrate via adenylation with Mg-ATP, resulting in an aminoacyl adenylated intermediate. Around 550 amino acids make up domain A. It has 10 amino acid residues that serve as NRPS enzyme “codons” and are essential for substrate specificity. The D and L forms of the 20 amino acids used in ribosomal protein synthesis, as well as non-proteinogenic amino acids like imino acids, ornithine, and hydroxy acids like β-butyric acids and α-aminoadipic, are substrates recognized by the A-domain. The PCP-domain, which consists of about 80 amino acids and covalently attaches the activated amino acid to their cofactor 4′-phosphopantetheine (PP) arm via a thioester bond, completes the second step. And also, the active substrate and elongation intermediates are transferred to the C-domain via this domain. In the last step, C-domain, which contains approximately 450 amino acids, catalyzes the formation of peptide bonds between the carboxyl group of the incipiently synthesized peptide and the amino acid transported by the side module [5, 22]. Furthermore, this domain allows the expanding chain to be translocated to the next module. Following this step, the linear intermediate peptide is liberated in bacteria via internal cyclization or hydrolysis with the help of the Thioesterase (TE) domain. On the other hand, it appears less commonly in fungi’s NRPSs. Fungi use a variety of ways to release chains. The first is a thioesterase NADP(H)-dependent reductase domain (R), which catalyzes NADPH reduction to create an aldehyde and the second is a terminal C domain, which catalyzes release by forming intermolecular or intramolecular amide bonds. By N-, C-, and O-methylation, halogenation, acylation, hydroxylation, glycosylation, or heterocyclic ring formation, the primary product of this synthesis can be changed post-synthetically to reach its mature form by additional tailoring enzymes that are not part of the NRPS. The structural diversity of NRPs is formed in part by these enzymes and their reactions [5].
Because of their extensive multidomain organization, NRPS genes are easier to identify using recent genome mining technologies, and they are also relatively easy to detect. Secondary metabolites production genes are frequently found in bacterial and fungal gene clusters. The clusters’ core is thought to be NRPS genes. Nevertheless, they are linked to genes involved in building blocks synthesis, product ornamentation, self-resistance, and peptide export. For the purpose of analyzing and in silico exploration of NRPS pathways, advanced genome sequencing techniques have made genome mining methodologies available, which are assisted by a variety of bioinformatics tools, such as AntiSMASH, PRISM, and SMURF [23].
Nowadays, known NRP structures are divided into various categories, each with its own structural characteristics. Lipocyclopeptides with varied linkage patterns, such as fengycin, iturin, surfactin, and head-to-tail-cyclized peptides of varying ring sizes, such as cyclosporine, gramicidin S, maybe the largest group. There are also a lot of linear peptide configurations. They include tripeptides (such as sevadicin and bialaphos) as well as 20-mer peptides (e.g., alamethicin, peptaibols). The current highest size limit for NRPs is syringopeptin 25A, which has 25 amino acids (syringopeptin 25A). Tailoring enzymes modify the structure of some NRPs. The most structurally complicated molecules are probably bleomycins, ergopeptides, glycopeptide antibiotics, and β-lactams [23].
Figure 2 shows some NRPs with diverse structures and a wide spectrum of activities. ACV-tripeptide (6), for example, is a precursor to antibiotics of the penicillin and cephalosporin families. Gramicidin S (4), tyrocidine A (1), and vancomycin (5) are three other antibiotic-active substances. Cyclosporin A (7), an immunosuppressive drug, is used in the post-transplantation care of patients. Cancer is treated with cytostatic agents, such as bleomycin A2 (8) and epothilone (9). Enterobactin (10), bacillibactin (11), mixochelin A (12), yersiniabactin (13), and vibriobactin (14) are examples of iron chelating agents. These compounds, known as siderophores, are created in iron-deficient environments to provide bacteria with an iron source. Figure 2 also depicts the structures of pigments like indigodin (15), toxins like thaxtomin A (17), and peptides with uncertain functions like anabaenopeptilide 90-A (18) [14].
Some NRPs with structural diversity [
NRPs have a number of structural characteristics that distinguish them from ribosomal peptides. For example, non-proteinogenic amino acids, such as ornithine in 1, 2, and 4, hydroxyphenyl or dihydroxyphenyl-glycine in 5 and (4R)-4-[(E)-2-butenyl]-4-methyl-L. -threonine (Bmt) in 7, are included. Furthermore, the structures are frequently macrocyclic (1), branched macrocyclic (2), or dimers of two (4) or trimers of three (10, 11) structural components. Smaller heterocyclic rings, such as thiazole in 9, thiazoline in 13, or oxazoline in 14, are common structural properties of nonribosomal peptides. In addition, fatty acids (3), glycosylations (5), N-methylations (7), and N-formylations (18) may also be present, as well as the addition of propionate units (8) or acetate [14].
NRPs are typically produced by marine microorganisms, soil-inhabiting microorganisms, including
Novel peptide products’ biological functions are strictly associated with their chemical structure, which is constrained by a peptide sequence that ensures specific interaction with a specific molecular target. Chemical alterations, such as the incorporation of fatty acid chains, D-amino acids, glycosylated amino acids, and heterocyclic rings, as well as cyclization or oxidative cross-linking of side chains, add a lot to these unique interactions. Bacitracin, fengycin, pristinamycin, surfactin, tyrocidine, and vancomycin are examples of novel peptides with antibacterial and antifungal properties [25].
When the ribosomal code was deciphered in the 1960s, Tatum and coworkers discovered that ribosomes had no effect on cell-based tyrocidine production [23, 26]. The first NRPs agent is tyrocidine, a cyclic decapeptide that is biosynthesized outside of the
Compound | Biosynthetic class of agent | Source | Disease/Molecular target |
---|---|---|---|
Bacitracin | Cyclic peptide | Antibiotic/dephosphorylation of C55-isoprenyl pyrophosphate | |
Bleomycin | Hybrid peptide | Antibiotic/inhibition of DNA synthesis | |
Capreomycin | Cyclicpeptide | Antibiotic/protein synthesis inhibitor | |
Carbapenems | Synthetic thienamycin | Antibacterial (multidrug resistant)/bacterial cell-wall biosynthesis (peptidoglycan;β-lactamase inhibition) | |
Cephalosporin | Antibiotic/Alters bacterial outer membrane | ||
Chlorampheniol | Synthetic;further derivatives: thiamphenicol [c], florfenicol | Antibacterial/inhibition of ribosomal protein synthesis | |
Colistin (Polymyxin E) | — | Antibacterial/binding to lipopolysaccharide (outer membrane), interaction with the cytoplasmic membrane | |
Dalbavancin | Semisynthetic teicoplanin derivative | — | Antibacterial (Gram-positive)/membrane anchoring; disruption of cell membrane and inhibition of bacterial cell wall biosynthesis |
Daptomycin | Lipopeptide | Antibiotic (Gram-positive)/disrupts the cell membrane | |
Gramicidin | Linear pentadecapeptide | Antibiotic/ion-channel formation, increasing the permeability of the membrane | |
Lincomycin | — | Antibacterial (patients allergic to penicillin) inhibition of the ribosomal protein synthesis (50S-subunit, dissociation of peptidyl-tRNA from the ribosome) | |
Monobactams | — | Antibacterial (Gram-negative)/bacterial cell-wall biosynthesis | |
Oritavancin | — | Semi synthetic | Antibiotic/disrupts the cell membrane |
Polymyxin B | Polypeptides | Antibacterial (Gram-negative)/binding to lipopolysaccharide (outer membrane), interaction with cytoplasmic membrane | |
Pristinamycin | Depsipeptide | Antibacterial (Gram-positive)/ribosomal biosynthesis (50S-subunit, peptidyl transfer, and elongation of protein synthesis) | |
Teicoplanin | Glycopeptide | Antibiotic/inhibit cell wall synthesis | |
Telavancin | — | Antibacterial (Gram-positive) disruption of cell membrane and inhibition of bacterial cell-wall biosynthesis | |
Tyrothricin | — | Antibacterial (Gram-positive)/disruption of cell membrane | |
Vancomycin | Glycopeptide | Antibiotic/inhibit cell wall synthesis | |
Virginiamycin | — | Antibacterial/ribosomal biosynthesis (50S-subunit, peptidyl transfer, and elongation of protein synthesis) |
As demonstrated in Table 2, systemic and topical antibacterials are the most often used NRPs-based drugs, accounting for billions of dollars in the chemical and pharmaceutical industry sales. Table 3 lists their other applications, which include anticancer agents, antifungals, animal feed additives, immunosuppressants (cyclosporine), obstetrics (ergometrine), and pain management (ergotamine).
Agent | Origin | Properties and area of application |
---|---|---|
Actinomycin D (Dactinomycin) | Antitumor/DNA intercalator, inhibition of transcription | |
Bialaphos | Herbicide/tripeptide prodrug, inhibitor of glutamine synthetase | |
Bleomycin A2, B2 | Antitumor/metal-dependent oxidative cleavage of DNA in presence of molecular oxygen | |
Capreomycin | Antituberculous/ inhibition of the ribosomal protein synthesis (16S and 23S-rRNA) | |
Carfilzomib | Synthetic derivative of epoxomycin ( | Anticancer/proteasome inhibitor |
Caspofungin | Antifungal (candidiasis, aspergillosis) fungal cell-wall integrity ((1-3)-β-D-glucan synthase) | |
Cyclosporine A | Immunosuppressant/cyclophilin binding, inhibition of IL-2 expression (inhibition of T-cell activation) | |
Emodepside | Anthelmintic/Slo-1 receptor (K+ channel) | |
Enduracidin (Enramycin) | Antibacterial, food additive/inhibition of MurG (essential for cell-wall biosynthesis in Gram positive bacteria), inhibition of the transglycosylation step of peptidoglycan biosynthesis | |
Enniatins (fusafungine) | Antibacterial (topical), antifungal, anti-inflammatory/ ionophore (NH4+) membrane depolarization | |
Ergometrine (ergonovine) | Obstetrics/interaction with a-adrenergic, dopaminergic and serotonin receptors | |
Ergotamine | Migraine vasoconstrictive (5-HT1B receptor, but also dopamine and noradrenaline receptors) | |
Romidepsin | Antitumor/histone deacetylase inhibitor (inducing apoptosis) | |
Trabectedin | Bacterial symbiont of | Antitumor (antiproliferative, treatment of soft tissue sarcoma) DNA binder, blocks binding of transcription factors |
Marketed-NRPs agents [23].
In the medical field, NRP-based marketed drugs, such as Cyclosporin A and Bleomycin A2, have high selling prices. The cost of these medicines is $107 for 25 mg of Cyclosporine A (98% purity) obtained from
The 70% discovery of NRPs with antibacterial, antiviral, cytostatic, immunosuppressive, antimalarial, antiparasitic, animal growth promoters, and natural insecticides activity is mostly attributed to marine organisms [13]. NRPs obtained from marine organisms (sponges, tunicates, and their associated phyla, such as Acidobacteria, Actinobacteria, Bacteriodetes, Chloroflexi, Cyanobacteria, Nitrospira, Planctomycetes, Poribacteria, Proteobacteria, Verrucomicrobia, and Archaea) have excellent binding properties, low off-target toxicity, and high stability and these properties make them a promising molecule for the development of new therapeutics pharmacologically active in many clinical searches. Table 4 shows the chemical structure and source of various NRPs isolated from marine sponges and tunicates.
NRPs agents | Chemical class | Origin | Target |
---|---|---|---|
Miraziridine A | Linear pentapeptide | Cancer/inhibit protease cathepsin B | |
Haligramides A-B | Cyclic hexapeptides | Cancer/A-549 (lung), HCT-15 (colon), SF-539 (CNS), SNB-19 (CNS) | |
Prepatellamide A | Cyclic peptide | Cancer/P388 murine leukemia cell lines | |
Tamandarins A-B | Depsipeptides | Cancer/pancreatic carcinoma BX-PC3, prostatic cancer DU-145, head and neck carcinoma UMSCC10b | |
Microsclerodermins F–I | Cyclic peptides | Cancer/HCT-116 cell line | |
Wainunuamide | Cyclic hexapeptide | Cancer/A2780 ovarian, K562 leukemia cancer cells | |
Leucamide A | Cyclic hexapeptide | Cancer/Tumor cell lines HM02, HepG2, Huh7 | |
Axinellin C | Cyclic octapeptide | Cancer/A2780 ovarian, K562 leukemia cancer cells | |
Milnamide D | Linearpeptide | Cancer/HCT-116 cells | |
Kapakahines E–G | — | Cancer/P388 murine leukemia cells | |
Didmolamides A-B | Cyclic hexapeptides | Cancer Tumor cell lines (A549, HT29 and MEL28) | |
Bistratamides E–J | Cyclic hexapeptides | Cancer/Human colon tumor (HCT-116) cell line | |
Milnamide C | — | Cancer/MDA-MB-435cancer cells | |
Scleritodermin A | Cyclic peptide | Cancer | |
Microcionamids A-B | — | Cancer/Human breast tumor cell lines MCF-7 and SKBR-3 | |
Kendarimide A | Linear peptide | Cancer/KB-C2 cells | |
Phakellistatin 14 | Cyclo heptapeptide | Cancer/Murine lymphocytic leukemia P388 cell line | |
Polytheonamides A-B | Polypeptides | Cancer/P388 murine leukemia cells | |
Neopetrosiamides A-B | Tricyclic peptides | Cancer | |
Seragamides A–F | Depsipeptides | Cancer | |
Theopapuamide | Cyclic depsipeptide | Cancer/CEM-TART, HCT-116 cell lines | |
Azumamide A-E | Cyclo tetrapeptides | Cancer | |
Callyaerin G | Cyclic peptide | Cancer/Mouselymphoma cell line (L5178Y) and HeLa cells | |
Stylopeptide 2 | Cyclo decapeptide | Cancer/BT-549 and HS578T breast cancer cell lines | |
Ciliatamides A-C | Lipopeptides | Cancer/HeLa cells | |
Diazonamides C–E | Macrocyclic peptides | Cancer/Human tumor cell lines (A549, HT29, MDA-MB231) | |
Rolloamide A-B | Cyclic heptapeptides | Cancer | |
Euryjanicin A | Cycloheptapeptide | Cancer | |
Callyaerin A–F and H | Cyclic peptides | Cancer/L5178Y cell line | |
Papuamides E-F | Depsipeptides | Cancer/Brine shrimp | |
Stylissamide X | Octapeptide | Cancer/HeLa cells | |
Gombamide A | Hexapeptide | Cancer/K562 and A549 cell lines | |
Microspinosamide | Cyclic depsipeptide | HIV | |
Neamphamide A | Cyclic depsipeptide | HIV | |
Mirabamides A-D | Cyclic depsipeptide | HIV | |
Homophymine A | Cyclodepsipeptide | HIV/PBMC cell line | |
Celebeside A-C | Depsipeptides | HIV/Colon carcinoma (HCT-116) cells | |
Theopapuamides B–D, Mutremdamide A, Koshikamides C-H | Cyclic depsipeptide | HIV | |
Ceratospongamide | Cyclic heptapeptide | Inflammation | |
Halipeptin A-B | Cyclic depsipeptide | Inflammation | |
Perthamide C-D | Cyclopeptide | Inflammation | |
Solomonamide A- B | Cyclic peptide | Inflammation | |
Stylissatin A | Cyclic peptide | Murine macrophage RAW264.7 | |
Dicynthaurin | — | Antimicrobial | |
Nagahamide A | Depsipeptide | Antibacterial | |
Plicatamide | Octapeptide | Antimicrobial | |
Callipeltins | — | ||
Citronamides A- B | — | ||
Renieramide | Cyclic tripeptide | — | |
Phoriospongins A-B | Depsipeptide | Nematocidal/ |
Agents produced from marine sponges and tunicates which are based on NRPs [7].
In the NCBI database, there are currently about 1.164 distinct non-ribosomal peptides that form over 500 different monomers including both proteinogenic and non-proteinogenic L- and D-amino acids, as well as amines and carboxylic acids. These complex secondary metabolites’ linear, cyclic, branching, or other complicated primary structures are frequently altered to enhance clinical qualities and/or bypass resistance mechanisms. Indeed, the nucleotide sequence modification of a native NRPS gene or mixing modules from multiple NRPSs makes them more efficient with pharmacological properties. Several bioengineering and molecular techniques have been developed during the last few decades to produce modified NRPs with improved physicochemical characteristics and bioactivity [13].
In this chapter, we discussed the significance, synthesis, and application areas of NRPs-based agents, which have received a lot of interest as a new source of pharmaceutical agents. NRPs with unique chemical structures and diverse biological actions, such as antibacterials (penicillin, vancomycin), anticancer compounds (bleomycin), and immunosuppressants (cyclosporine), have been researched as novel compounds for new drug discovery and development throughout the last several decades.
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Mainly, the versatile techniques of ultra−/high-performance liquid chromatography (UPLC/HPLC) are in use for the analysis of assay and organic impurities/related substances/degradation products of a drug substance or drug product or intermediate or raw material of pharmaceuticals. A suitable analytical method is developed only after evaluating the major and critical separation parameters of chromatography (examples for UPLC/HPLC are selection of diluent, wavelength, detector, stationary phase, column temperature, flow rate, solvent system, elution mode, and injection volume, etc.). The analytical method development is a process of proving the developed analytical method is suitable for its intended use for the quantitative estimation of the targeted analyte present in pharmaceutical drugs. And it mostly plays a vital role in the development and manufacture of pharmaceuticals drugs.",book:{id:"8912",slug:"biochemical-analysis-tools-methods-for-bio-molecules-studies",title:"Biochemical Analysis Tools",fullTitle:"Biochemical Analysis Tools - Methods for Bio-Molecules Studies"},signatures:"Narasimha S. 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RNA‐seq data analyses typically consist of (1) accurate mapping of millions of short sequencing reads to a reference genome, including the identification of splicing events; (2) quantifying expression levels of genes, transcripts, and exons; (3) differential analysis of gene expression among different biological conditions; and (4) biological interpretation of differentially expressed genes. Despite the fact that multiple algorithms pertinent to basic analyses have been developed, there are still a variety of unresolved questions. In this chapter, we review the main tools and algorithms currently available for RNA‐seq data analyses, and our goal is to help RNA‐seq data analysts to make an informed choice of tools in practical RNA‐seq data analysis. In the meantime, RNA‐seq is evolving rapidly, and newer sequencing technologies are briefly introduced, including stranded RNA‐seq, targeted RNA‐seq, and single‐cell RNA‐seq.",book:{id:"5160",slug:"bioinformatics-updated-features-and-applications",title:"Bioinformatics",fullTitle:"Bioinformatics - Updated Features and Applications"},signatures:"Shanrong Zhao, Baohong Zhang, Ying Zhang, William Gordon,\nSarah Du, Theresa Paradis, Michael Vincent and David von Schack",authors:[{id:"176364",title:"Dr.",name:"Shanrong",middleName:null,surname:"Zhao",slug:"shanrong-zhao",fullName:"Shanrong Zhao"}]},{id:"49873",title:"An Introduction to Actinobacteria",slug:"an-introduction-to-actinobacteria",totalDownloads:8089,totalCrossrefCites:29,totalDimensionsCites:101,abstract:"Actinobacteria, which share the characteristics of both bacteria and fungi, are widely distributed in both terrestrial and aquatic ecosystems, mainly in soil, where they play an essential role in recycling refractory biomaterials by decomposing complex mixtures of polymers in dead plants and animals and fungal materials. They are considered as the biotechnologically valuable bacteria that are exploited for its secondary metabolite production. Approximately, 10,000 bioactive metabolites are produced by Actinobacteria, which is 45% of all bioactive microbial metabolites discovered. Especially Streptomyces species produce industrially important microorganisms as they are a rich source of several useful bioactive natural products with potential applications. Though it has various applications, some Actinobacteria have its own negative effect against plants, animals, and humans. On this context, this chapter summarizes the general characteristics of Actinobacteria, its habitat, systematic classification, various biotechnological applications, and negative impact on plants and animals.",book:{id:"5056",slug:"actinobacteria-basics-and-biotechnological-applications",title:"Actinobacteria",fullTitle:"Actinobacteria - Basics and Biotechnological Applications"},signatures:"Ranjani Anandan, Dhanasekaran Dharumadurai and Gopinath\nPonnusamy Manogaran",authors:[{id:"48914",title:"Dr.",name:"Dharumadurai",middleName:null,surname:"Dhanasekaran",slug:"dharumadurai-dhanasekaran",fullName:"Dharumadurai Dhanasekaran"}]},{id:"72074",title:"The Chemistry Behind Plant DNA Isolation Protocols",slug:"the-chemistry-behind-plant-dna-isolation-protocols",totalDownloads:3691,totalCrossrefCites:3,totalDimensionsCites:5,abstract:"Various plant species are biochemically heterogeneous in nature, a single deoxyribose nucleic acid (DNA) isolation protocol may not be suitable. There have been continuous modification and standardization in DNA isolation protocols. Most of the plant DNA isolation protocols used today are modified versions of hexadecyltrimethyl-ammonium bromide (CTAB) extraction procedure. Modification is usually performed in the concentration of chemicals used during the extraction procedure according to the plant species and plant part used. Thus, understanding the role of each chemical (viz. CTAB, NaCl, PVP, ethanol, and isopropanol) used during the DNA extraction procedure will benefit to set or modify protocols for more precisions. A review of the chemicals used in the CTAB method of DNA extraction and their probable functions on the highly evolved yet complex to students and researchers has been summarized.",book:{id:"8912",slug:"biochemical-analysis-tools-methods-for-bio-molecules-studies",title:"Biochemical Analysis Tools",fullTitle:"Biochemical Analysis Tools - Methods for Bio-Molecules Studies"},signatures:"Jina Heikrujam, Rajkumar Kishor and Pranab Behari Mazumder",authors:[{id:"74521",title:"Dr.",name:"Rajkumar",middleName:null,surname:"Kishor",slug:"rajkumar-kishor",fullName:"Rajkumar Kishor"},{id:"309357",title:"Prof.",name:"Pranab Behari",middleName:null,surname:"Mazumder",slug:"pranab-behari-mazumder",fullName:"Pranab Behari Mazumder"},{id:"318351",title:"Ph.D. Student",name:"Jina",middleName:null,surname:"Heikrujam",slug:"jina-heikrujam",fullName:"Jina Heikrujam"}]}],onlineFirstChaptersFilter:{topicId:"6",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"82195",title:"Endoplasmic Reticulum: A Hub in Lipid Homeostasis",slug:"endoplasmic-reticulum-a-hub-in-lipid-homeostasis",totalDownloads:1,totalDimensionsCites:null,doi:"10.5772/intechopen.105450",abstract:"Endoplasmic Reticulum (ER) is the largest and one of the most complex cellular structures, indicating its widespread importance and variety of functions, including synthesis of membrane and secreted proteins, protein folding, calcium storage, and membrane lipid biogenesis. Moreover, the ER is implicated in cholesterol, plasmalogen, phospholipid, and sphingomyelin biosynthesis. Furthermore, the ER is in contact with most cellular organelles, such as mitochondria, peroxisomes, Golgi apparatus, lipid droplets, plasma membrane, etc. Peroxisomes are synthesized from a specific ER section, and they are related to very-long-chain fatty acid metabolism. Similarly, lipid droplets are vital structures in lipid homeostasis that are formed from the ER membrane. Additionally, there is a specific region between the ER-mitochondria interface called Mitochondria-Associated Membranes (MAMs). This small cytosolic gap plays a key role in several crucial mechanisms from autophagosome synthesis to phospholipid transfer. Due to the importance of the ER in a variety of biological processes, alterations in its functionality have relevant implications for multiple diseases. Nowadays, a plethora of pathologies like non-alcoholic steatohepatitis (NASH), cancer, and neurological alterations have been associated with ER malfunctions.",book:{id:"11674",title:"Updates on Endoplasmic Reticulum",coverURL:"https://cdn.intechopen.com/books/images_new/11674.jpg"},signatures:"Raúl Ventura and María Isabel Hernández-Alvarez"},{id:"82409",title:"Purinergic Signaling in Covid-19 Disease",slug:"purinergic-signaling-in-covid-19-disease",totalDownloads:2,totalDimensionsCites:0,doi:"10.5772/intechopen.105008",abstract:"SARS-CoV-2 virus infection causes the Covid-19 disease pandemic. Purinergic signaling is a form of extracellular signaling. Purinergic signaling plays significant role in the pathology of Covid-19. Purinergic system includes extracellular nucleotides, nucleosides, ectonucleotidases, and purinergic receptors. ATP, ADP, and adenosine are the main nucleotides, nucleosides. CD39 and CD73 are the main ectonucleotidases. There are two classes of purinergic receptors, P1 and P2. Each of them can be further divided, P1 into A1, A2A, A2B, and A3, P2 into P2X, and P2Y. In Covid-19, the purinergic system is disordered. SARS-CoV-2 viruses invading leads to extracellular ATP and ADP accumulation, purinergic receptor abnormally activation, tissue homeostasis balance is broken, which lead to inflammation even hyperinflammation with cytokine storm and thrombosis et al. symptoms. Currently, Covid-19 therapeutic medicine is still in shortage. Target purinergic system components is a promising way to treat Covid-19, which will help inhibit inflammation and prevent thrombosis. Currently, many relevant preclinical and clinical trials are ongoing. Some are very promising.",book:{id:"10801",title:"Purinergic System",coverURL:"https://cdn.intechopen.com/books/images_new/10801.jpg"},signatures:"Hailian Shen"},{id:"81708",title:"High Throughput Methods to Transfer DNA in Cells and Perspectives",slug:"high-throughput-methods-to-transfer-dna-in-cells-and-perspectives",totalDownloads:5,totalDimensionsCites:0,doi:"10.5772/intechopen.104542",abstract:"Genome sequencing led to thousands of genes to study and their molecular cloning to provide ORF collection plasmids. The main approach to study their function involves analysis of the biological consequences of their expression or knockdown, in a cellular context. Given that, the starting point of such experiments is the delivery of the exogenous material, including plasmid DNA in cells. During the last decades, efforts were made to develop efficient methods and protocols to achieve this goal. The present chapter will first give a rapid overview of the main DNA transfer methods described so far: physical, chemical, and biological. Secondly, it will focus on the different methods having reached high-throughput nowadays. Finally, it will discuss the perspectives of this field in terms of future enhancements.",book:{id:"11356",title:"Molecular Cloning",coverURL:"https://cdn.intechopen.com/books/images_new/11356.jpg"},signatures:"Colin Béatrice and Couturier Cyril"},{id:"82374",title:"The Potential of the Purinergic System as a Therapeutic Target of Natural Compounds in Cutaneous Melanoma",slug:"the-potential-of-the-purinergic-system-as-a-therapeutic-target-of-natural-compounds-in-cutaneous-mel",totalDownloads:7,totalDimensionsCites:0,doi:"10.5772/intechopen.105457",abstract:"Cutaneous melanoma is an aggressive and difficult-to-treat disease that has rapidly grown worldwide. The pharmacotherapy available in so many cases results in low response and undesirable side effects, which impair the life quality of those affected. Several studies have been shown that the purinergic system is involved in cancer context, such as in cutaneous melanoma. With technological advances, several bioactive compounds from nature are studied and presented as promising adjuvant therapies against cancer, as phenolic compounds and related action by purinergic system modulations. Thus, phenolic compounds such as rosmarinic acid, resveratrol, tannic acid, as well as vitamin D may be promising substances in a therapeutic perspective to treat cutaneous melanoma via purinergic system pathway. More research needs to be done to open up new horizons in the treatment of melanoma by the purinergic signaling.",book:{id:"10801",title:"Purinergic System",coverURL:"https://cdn.intechopen.com/books/images_new/10801.jpg"},signatures:"Gilnei Bruno da Silva, Daiane Manica, Marcelo Moreno and Margarete Dulce Bagatini"},{id:"82338",title:"Advantages of Noncoding RNAs in Molecular Diagnosis",slug:"advantages-of-noncoding-rnas-in-molecular-diagnosis",totalDownloads:7,totalDimensionsCites:0,doi:"10.5772/intechopen.105525",abstract:"Noncoding RNAs contribute to physiological processes by regulating many intracellular molecules participating in the life-supporting mechanisms of development, differentiation, and regeneration as well as by disrupting various signaling mechanisms such as disease development and progression and tumor growth. Because microRNAs (miRNAs) target and regulate the functions of key proteins, it is very useful to identify specific miRNAs that contribute to cellular functions and to clarify the roles of their target molecules as diagnostic and therapeutic strategies for cancer prognosis and treatment. 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Thus proteomics, an area of research that detects all protein forms expressed in an organism, including splice isoforms and post-translational modifications, is more suitable than genomics for a comprehensive understanding of the biochemical processes that govern life. The most common proteomics applications are currently in the clinical field for the identification, in a variety of biological matrices, of biomarkers for diagnosis and therapeutic intervention of disorders. From the comparison of proteomic profiles of control and disease or different physiological states, which may emerge, changes in protein expression can provide new insights into the roles played by some proteins in human pathologies. Understanding how proteins function and interact with each other is another goal of proteomics that makes this approach even more intriguing. Specialized technology and expertise are required to assess the proteome of any biological sample. 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