The advent of next generation sequencing (NGS) has enabled investigations of the gut microbiome with unprecedented resolution and throughput. This has stimulated the development of sophisticated ...bioinformatics tools to analyze the massive amounts of data generated. Researchers therefore need a clear understanding of the key concepts required for the design, execution and interpretation of NGS experiments on microbiomes. We conducted a literature review and used our own data to determine which approaches work best. The two main approaches for analyzing the microbiome, 16S ribosomal RNA (rRNA) gene amplicons and shotgun metagenomics, are illustrated with analyses of libraries designed to highlight their strengths and weaknesses. Several methods for taxonomic classification of bacterial sequences are discussed. We present simulations to assess the number of sequences that are required to perform reliable appraisals of bacterial community structure. To the extent that fluctuations in the diversity of gut bacterial populations correlate with health and disease, we emphasize various techniques for the analysis of bacterial communities within samples (α-diversity) and between samples (β-diversity). Finally, we demonstrate techniques to infer the metabolic capabilities of a bacteria community from these 16S and shotgun data.
Machine learning (ML) approaches are a collection of algorithms that attempt to extract patterns from data and to associate such patterns with discrete classes of samples in the data-e.g., given a ...series of features describing persons, a ML model predicts whether a person is diseased or healthy, or given features of animals, it predicts weather an animal is treated or control, or whether molecules have the potential to interact or not, etc. ML approaches can also find such patterns in an agnostic manner, i.e., without having information about the classes. Respectively, those methods are referred to as supervised and unsupervised ML. A third type of ML is reinforcement learning, which attempts to find a sequence of actions that contribute to achieving a specific goal. All of these methods are becoming increasingly popular in biomedical research in quite diverse areas including drug design, stratification of patients, medical images analysis, molecular interactions, prediction of therapy outcomes and many more. We describe several supervised and unsupervised ML techniques, and illustrate a series of prototypical examples using state-of-the-art computational approaches. Given the complexity of reinforcement learning, it is not discussed in detail here, instead, interested readers are referred to excellent reviews on that topic. We focus on concepts rather than procedures, as our goal is to attract the attention of researchers in biomedicine toward the plethora of powerful ML methods and their potential to leverage basic and applied research programs.
Off-target DNA cleavage is a paramount concern when applying CRISPR-Cas9 gene-editing technology to functional genetics and human therapeutic applications. Here, we show that incorporation of ...next-generation bridged nucleic acids (2',4'-BNA
N-Me) as well as locked nucleic acids (LNA) at specific locations in CRISPR-RNAs (crRNAs) broadly reduces off-target DNA cleavage by Cas9 in vitro and in cells by several orders of magnitude. Using single-molecule FRET experiments we show that BNA
incorporation slows Cas9 kinetics and improves specificity by inducing a highly dynamic crRNA-DNA duplex for off-target sequences, which shortens dwell time in the cleavage-competent, "zipped" conformation. In addition to describing a robust technique for improving the precision of CRISPR/Cas9-based gene editing, this study illuminates an application of synthetic nucleic acids.
Cell-surface transferrin receptor (CD71+) erythroid cells are abundant in newborns with immunomodulatory properties. Here, we show that neonatal CD71+ erythroid cells express significant levels of ...V-domain Immunoglobulin (Ig) Suppressor of T Cell Activation (VISTA) and, via constitutive production of transforming growth factor (TGF)- β, play a pivotal role in promotion of naïve CD4+ T cells into regulatory T cells (Tregs). Interestingly, we discovered that CD71+VISTA+ erythroid cells produce significantly higher levels of TGF-β compared to CD71+VISTA- erythroid cells and CD71+ erythroid cells from the VISTA knock-out (KO) mice. As a result, CD71+VISTA+ erythroid cells-compared to CD71+VISTA- and CD71+ erythroid cells from the VISTA KO mice-significantly exceed promotion of naïve CD4+ T cells into induced Tregs (iTreg) via TGF-β in vitro. However, depletion of CD71+ erythroid cells had no significant effects on the frequency of Tregs in vivo. Surprisingly, we observed that the remaining and/or newly generated CD71+ erythroid cells following anti-CD71 antibody administration exhibit a different gene expression profile, evidenced by the up-regulation of VISTA, TGF-β1, TGF-β2, and program death ligand-1 (PDL-1), which may account as a compensatory mechanism for the maintenance of Treg population. We also observed that iTreg development by CD71+ erythroid cells is mediated through the inhibition of key signaling molecules phosphorylated protein kinase B (phospho-Akt) and phosphorylated mechanistic target of rapamycin (phospho-mTOR). Finally, we found that elimination of Tregs using forkhead box P3 (FOXP3)-diptheria toxin receptor (DTR) mice resulted in a significant expansion in the frequency of CD71+ erythroid cells in vivo. Collectively, these studies provide a novel, to our knowledge, insight into the cross-talk between CD71+ erythroid cells and Tregs in newborns. Our results highlight the biological role of CD71+ erythroid cells in the neonatal period and possibly beyond.
CRISPR/Cas complexes enable precise gene editing in a wide variety of organisms. While the rigid identification of DNA sequences by these systems minimizes the potential for off-target effects, it ...consequently poses a problem for the recognition of sequences containing naturally occurring polymorphisms. The presence of genetic variance such as single nucleotide polymorphisms (SNPs) in a gene sequence can compromise the on-target activity of CRISPR systems. Thus, when attempting to target multiple variants of a human gene, or evolved variants of a pathogen gene using a single guide RNA, more flexibility is desirable. Here, we demonstrate that Cas9 can tolerate the inclusion of universal bases in individual guide RNAs, enabling simultaneous targeting of polymorphic sequences. Crucially, we find that specificity is selectively degenerate at the site of universal base incorporation, and remains otherwise preserved. We demonstrate the applicability of this technology to targeting multiple naturally occurring human SNPs with individual guide RNAs and to the design of Cas12a/Cpf1-based DETECTR probes capable of identifying multiple evolved variants of the HIV protease gene. Our findings extend the targeting capabilities of CRISPR/Cas systems beyond their canonical spacer sequences and highlight a use of natural and synthetic universal bases.
The interaction of neutrophils with T cells has been the subject of debate and controversies. Previous studies have suggested that neutrophils may suppress or activate T cells. Despite these studies, ...the interaction between neutrophils and T cells has remained a largely unexplored field. Here, based on our RNA sequencing (RNA-seq) analysis, we found that neutrophils have differential transcriptional and functional profiling depending on the CD4 T-cell count of the HIV-infected individual. In particular, we identified that neutrophils in healthy individuals express surface Galectin-9 (Gal-9), which is down-regulated upon activation, and is consistently down-regulated in HIV-infected individuals. However, down-regulation of Gal-9 was associated with CD4 T-cell count of patients. Unstimulated neutrophils express high levels of surface Gal-9 that is bound to CD44, and, upon stimulation, neutrophils depalmitoylate CD44 and induce its movement out of the lipid raft. This process causes the release of Gal-9 from the surface of neutrophils. In addition, we found that neutrophil-derived exogenous Gal-9 binds to cell surface CD44 on T cells, which promotes LCK activation and subsequently enhances T-cell activation. Furthermore, this process was regulated by glycolysis and can be inhibited by interleukin (IL)-10. Together, our data reveal a novel mechanism of Gal-9 shedding from the surface of neutrophils. This could explain elevated plasma Gal-9 levels in HIV-infected individuals as an underlying mechanism of the well-characterized chronic immune activation in HIV infection. This study provides a novel role for the Gal-9 shedding from neutrophils. We anticipate that our results will spark renewed investigation into the role of neutrophils in T-cell activation in other acute and chronic conditions, as well as improved strategies for modulating Gal-9 shedding.
Arabidopsis thaliana defense against distinct positive-strand RNA viruses requires production of virus-derived secondary small interfering RNAs (siRNAs) by multiple RNA-dependent RNA polymerases. ...However, little is known about the biogenesis pathway and effector mechanism of viral secondary siRNAs. Here, we describe a mutant of Cucumber mosaic virus (CMV-∆2b) that is silenced predominantly by the RNA-DEPENDENT RNA POLYMERASE6 (RDR6)-dependent viral secondary siRNA pathway. We show that production of the viral secondary siRNAs targeting CMV-∆2b requires SUPPRESSOR OF GENE SILENCING3 and DICER-UKE4 (DCL4) in addition to RDR6. Examination of 25 single, double, and triple mutants impaired in nine ARGONAUTE (AGO) genes combined with coimmunoprecipitation and deep sequencing identifies an essential function for AGO1 and AGO2 in defense against CMV-∆2b, which act downstream the biogenesis of viral secondary siRNAs in a nonredundant and cooperative manner. Our findings also illustrate that dicing of the viral RNA precursors of primary and secondary siRNA is insufficient to confer virus resistance. Notably, although DCL2 is able to produce abundant viral secondary siRNAs in the absence of DCL4, the resultant 22-nucleotide viral siRNAs alone do not guide efficient silencing of CMV-∆2b. Possible mechanisms for the observed qualitative difference in RNA silencing between 21-and 22-nucleotide secondary siRNAs are discussed.
Stiffness in the tissue microenvironment changes in most diseases and immunological conditions, but its direct influence on the immune system is poorly understood. Here, we show that static tension ...impacts immune cell function, maturation, and metabolism. Bone-marrow-derived and/or splenic dendritic cells (DCs) grown in vitro at physiological resting stiffness have reduced proliferation, activation, and cytokine production compared with cells grown under higher stiffness, mimicking fibro-inflammatory disease. Consistently, DCs grown under higher stiffness show increased activation and flux of major glucose metabolic pathways. In DC models of autoimmune diabetes and tumor immunotherapy, tension primes DCs to elicit an adaptive immune response. Mechanistic workup identifies the Hippo-signaling molecule, TAZ, as well as Ca2+-related ion channels, including potentially PIEZO1, as important effectors impacting DC metabolism and function under tension. Tension also directs the phenotypes of monocyte-derived DCs in humans. Thus, mechanical stiffness is a critical environmental cue of DCs and innate immunity.
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•Environmental stiffness promotes DC inflammatory function•Tension primes DC metabolism, even without pattern recognition receptor input•TAZ bridges mechanosensory signals to DC metabolism and function•Tension directs phenotypes of human monocyte-derived DCs
The immune system is carefully tuned to respond to dangers in the environment. Chakraborty et al. show that environmental stiffness controls dendritic cell metabolism, phenotype, and inflammatory function through downstream Hippo-signaling mediators. The findings provide evidence for mechanical force as an integral node directing innate immune responses.
Prevotella: A Key Player in Ruminal Metabolism Betancur-Murillo, Claudia Lorena; Aguilar-Marín, Sandra Bibiana; Jovel, Juan
Microorganisms (Basel),
12/2022, Letnik:
11, Številka:
1
Journal Article
Recenzirano
Odprti dostop
Ruminants are foregut fermenters that have the remarkable ability of converting plant polymers that are indigestible to humans into assimilable comestibles like meat and milk, which are cornerstones ...of human nutrition. Ruminants establish a symbiotic relationship with their microbiome, and the latter is the workhorse of carbohydrate fermentation. On the other hand, during carbohydrate fermentation, synthesis of propionate sequesters H, thus reducing its availability for the ultimate production of methane (CH4) by methanogenic archaea. Biochemically, methane is the simplest alkane and represents a downturn in energetic efficiency in ruminants; environmentally, it constitutes a potent greenhouse gas that negatively affects climate change.
is a very versatile microbe capable of processing a wide range of proteins and polysaccharides, and one of its fermentation products is propionate, a trait that appears conspicuous in
strain 23. Since propionate, but not acetate or butyrate, constitutes an H sink, propionate-producing microbes have the potential to reduce methane production. Accordingly, numerous studies suggest that members of the genus
have the ability to divert the hydrogen flow in glycolysis away from methanogenesis and in favor of propionic acid production. Intended for a broad audience in microbiology, our review summarizes the biochemistry of carbohydrate fermentation and subsequently discusses the evidence supporting the essential role of
in lignocellulose processing and its association with reduced methane emissions. We hope this article will serve as an introduction to novice
researchers and as an update to others more conversant with the topic.
Ruminants burp massive amounts of methane into the atmosphere and significantly contribute to the deposition of greenhouse gases and the consequent global warming. It is therefore urgent to devise ...strategies to mitigate ruminant's methane emissions to alleviate climate change. Ruminal methanogenesis is accomplished by a series of methanogen archaea in the phylum Euryarchaeota, which piggyback into carbohydrate fermentation by utilizing residual hydrogen to produce methane. Abundance of methanogens, therefore, is expected to affect methane production. Furthermore, availability of hydrogen produced by cellulolytic bacteria acting upstream of methanogens is a rate-limiting factor for methane production. The aim of our study was to identify microbes associated with the production of methane which would constitute the basis for the design of mitigation strategies.
Moderate differences in the abundance of methanogens were observed between groups. In addition, we present three lines of evidence suggesting an apparent higher abundance of a consortium of Prevotella species in animals with lower methane emissions. First, taxonomic classification revealed increased abundance of at least 29 species of Prevotella. Second, metagenome assembly identified increased abundance of Prevotella ruminicola and another species of Prevotella. Third, metabolic profiling of predicted proteins uncovered 25 enzymes with homology to Prevotella proteins more abundant in the low methane emissions group.
We propose that higher abundance of ruminal Prevotella increases the production of propionic acid and, in doing so, reduces the amount of hydrogen available for methanogenesis. However, further experimentation is required to ascertain the role of Prevotella on methane production and its potential to act as a methane production mitigator.
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