Identification of genes required for the survival of B. fragilis using massive parallel sequencing of a saturated transposon mutant library

Unveiling the mysteries: Functional insights into hypothetical proteins from Bacteroides fragilis 638R

Humans benefit from a vast community of microorganisms in their gastrointestinal tract, known as the gut microbiota, numbering in the tens of trillions. An imbalance in the gut microbiota known as dysbiosis, can lead to changes in the metabolite profile, elevating the levels of toxins like Bacteroides fragilis toxin (BFT), colibactin, and cytolethal distending toxin. These toxins are implicated in the process of oncogenesis. However, a significant portion of the Bacteroides fragilis genome consists of functionally uncharacterized and hypothetical proteins. This study delves into the functional characterization of hypothetical proteins (HPs) encoded by the Bacteroides fragilis genome, employing a systematic in silico approach. A total of 379 HPs were subjected to a BlastP homology search against the NCBI non-redundant protein sequence database, resulting in 162 HPs devoid of identity to known proteins. CDD-Blast identified 106 HPs with functional domains, which were then annotated using Pfam, InterPro, SUPERFAMILY, SCANPROSITE, SMART, and CATH. Physicochemical properties, such as molecular weight, isoelectric point, and stability indices, were assessed for 60 HPs whose functional domains were identified by at least three of the aforementioned bioinformatic tools. Subsequently, subcellular localization analysis was examined and the gene ontology analysis revealed diverse biological processes, cellular components, and molecular functions. Remarkably, E1WPR3 was identified as a virulent and essential gene among the HPs. This study presents a comprehensive exploration of B. fragilis HPs, shedding light on their potential roles and contributing to a deeper understanding of this organism's functional landscape.

Randomly barcoded transposon mutant libraries for gut commensals I: Strategies for efficient library construction

Randomly barcoded transposon mutant libraries are powerful tools for studying gene function and organization, assessing gene essentiality and pathways, discovering potential therapeutic targets, and understanding the physiology of gut bacteria and their interactions with the host. However, construction of high-quality libraries with uniform representation can be challenging. In this review, we survey various strategies for barcoded library construction, including transposition systems, methods of transposon delivery, optimal library size, and transconjugant selection schemes. We discuss the advantages and limitations of each approach, as well as factors to consider when selecting a strategy. In addition, we highlight experimental and computational advances in arraying condensed libraries from mutant pools. We focus on examples of successful library construction in gut bacteria and their application to gene function studies and drug discovery. Given the need for understanding gene function and organization in gut bacteria, we provide a comprehensive guide for researchers to construct randomly barcoded transposon mutant libraries.

Bile acid fitness determinants of a Bacteroides fragilis isolate from a human pouchitis patient

Bacteroides fragilis comprises 1-5% of the gut microbiota in healthy humans but can expand to >50% of the population in ulcerative colitis (UC) patients experiencing inflammation. The mechanisms underlying such microbial blooms are poorly understood, but the gut of UC patients has physicochemical features that differ from healthy patients and likely impact microbial physiology. For example, levels of the secondary bile acid deoxycholate (DC) are highly reduced in the ileoanal J-pouch of UC colectomy patients. We isolated a B. fragilis strain from a UC patient with pouch inflammation (i.e. pouchitis) and developed it as a genetic model system to identify genes and pathways that are regulated by DC and that impact B. fragilis fitness in DC and crude bile. Treatment of B. fragilis with a physiologically relevant concentration of DC reduced cell growth and remodeled transcription of one-quarter of the genome. DC strongly induced expression of chaperones and select transcriptional regulators and efflux systems and downregulated protein synthesis genes. Using a barcoded collection of ≈50,000 unique insertional mutants, we further defined B. fragilis genes that contribute to fitness in media containing DC or crude bile. Genes impacting cell envelope functions including cardiolipin synthesis, cell surface glycosylation, and systems implicated in sodium-dependent bioenergetics were major bile acid fitness factors. As expected, there was limited overlap between transcriptionally regulated genes and genes that impacted fitness in bile when disrupted. Our study provides a genome-scale view of a B. fragilis bile response and genetic determinants of its fitness in DC and crude bile.

Genome-scale metabolic modeling of the human gut bacterium Bacteroides fragilis strain 638R

Bacteroides fragilis is a universal member of the dominant commensal gut phylum Bacteroidetes. Its fermentation products and abundance have been linked to obesity, inflammatory bowel disease, and other disorders through its effects on host metabolic regulation and the immune system. As of yet, there has been no curated systems-level characterization of B. fragilis' metabolism that provides a comprehensive analysis of the link between human diet and B. fragilis' metabolic products. To address this, we developed a genome-scale metabolic model of B. fragilis strain 638R. The model iMN674 contains 1,634 reactions, 1,362 metabolites, three compartments, and reflects the strain's ability to utilize 142 metabolites. Predictions made with this model include its growth rate and efficiency on these substrates, the amounts of each fermentation product it produces under different conditions, and gene essentiality for each biomass component. The model highlights and resolves gaps in knowledge of B. fragilis' carbohydrate metabolism and its corresponding transport proteins. This high quality model provides the basis for rational prediction of B. fragilis' metabolic interactions with its environment and its host.

Development and Clinical Application of a Multilocus Sequence Typing Scheme for Bacteroides fragilis Based on Whole-Genome Sequencing Data

Bacteroides fragilis is among the most abundant and pathogenic bacterial species in the gut microbiota and is associated with diarrheal disease in children, inflammatory bowel disease, and the development of colorectal cancer. It is increasingly resistant to potent antimicrobial agents such as carbapenems and metronidazole, making it among the most resistant anaerobic bacteria. These factors combined call for increased monitoring of B. fragilis and its population structure on a worldwide scale. Here, we present a possible solution through the development of a multilocus sequence typing scheme (MLST). The scheme is based on seven core gene fragments: groL (hsp60), rpoB, recA, dnaJ, rprX, prfA, and fusA. These gene fragments possess high discriminatory power while retaining concordance with whole core genome-based phylogenetic analysis. The scheme proved capable of differentiating B. fragilis isolates at the strain level. It offers a standardized method for molecular typing and can be applied to isolates from various sampling backgrounds, such as patient isolates, environmental samples, and strains obtained from food and animal sources. In total, 567 B. fragilis genomes were sequence typed and their isolate data collected. The MLST scheme clearly divided the B. fragilis population into two divisions based on the presence of the cfiA and cepA resistance genes. However, no other specific subpopulations within the analyzed genomes were found to be associated with any specific diseases or geographical location. With this MLST scheme, we hope to provide a powerful tool for the study and monitoring of B. fragilis on an international scale. IMPORTANCE Here, we present the first MLST scheme for Bacteroides fragilis, one of the most abundant pathogenic bacteria in the human gut microbiota. The scheme enables standard classification and monitoring of B. fragilis on a worldwide scale and groups the majority of current isolate data in one place. A more unified approach to the collection and analysis of B. fragilis data could provide crucial insights into how the pathogen operates and develops as a species. Close monitoring of B. fragilis is especially relevant, as it is increasingly resistant to potent antimicrobial agents and engages in horizontal gene transfer with other bacteria. Hopefully, this approach will guide new discoveries into how B. fragilis evolves and interacts with its human host. Additionally, the scheme could potentially be applied to other species of the genus Bacteroides.

Identification of discriminant features from stationary pattern of nucleotide bases and their application to essential gene classification

Introduction: Essential genes are essential for the survival of various species. These genes are a family linked to critical cellular activities for species survival. These genes are coded for proteins that regulate central metabolism, gene translation, deoxyribonucleic acid replication, and fundamental cellular structure and facilitate intracellular and extracellular transport. Essential genes preserve crucial genomics information that may hold the key to a detailed knowledge of life and evolution. Essential gene studies have long been regarded as a vital topic in computational biology due to their relevance. An essential gene is composed of adenine, guanine, cytosine, and thymine and its various combinations. Methods: This paper presents a novel method of extracting information on the stationary patterns of nucleotides such as adenine, guanine, cytosine, and thymine in each gene. For this purpose, some co-occurrence matrices are derived that provide the statistical distribution of stationary patterns of nucleotides in the genes, which is helpful in establishing the relationship between the nucleotides. For extracting discriminant features from each co-occurrence matrix, energy, entropy, homogeneity, contrast, and dissimilarity features are computed, which are extracted from all co-occurrence matrices and then concatenated to form a feature vector representing each essential gene. Finally, supervised machine learning algorithms are applied for essential gene classification based on the extracted fixed-dimensional feature vectors. Results: For comparison, some existing state-of-the-art feature representation techniques such as Shannon entropy (SE), Hurst exponent (HE), fractal dimension (FD), and their combinations have been utilized. Discussion: An extensive experiment has been performed for classifying the essential genes of five species that show the robustness and effectiveness of the proposed methodology.

The Application of Transposon Insertion Sequencing in Identifying Essential Genes in B. fragilis

Essential genes are those that are indispensable for the survival of organism under specific growth conditions. Investigating essential genes in pathogenic bacteria not only helps to understand vital biological networks but also provides novel targets for drug development. Availability of genetic engineering tools and high-throughput sequencing methods has enabled essential genes identification in many pathogenic gram-positive and gram-negative bacteria. Bacteroides fragilis is one of the major bacteria specific of human gastrointestinal microbiota. When B. fragilis moves out of its niche, it turns into deadly pathogen. Here, we describe detailed method for the essential gene identification in B. fragilis. Generated transposon mutant pool can be used for other applications such as identification of genes responsible for drug resistance in B. fragilis.

A Large Insertion Domain in the Rho Factor From a Low G + C, Gram-negative Bacterium is Critical for RNA Binding and Transcription Termination Activity

Rho-dependent termination of transcription (RDTT) is a critical regulatory mechanism specific to bacteria. In a subset of species including most Actinobacteria and Bacteroidetes, the Rho factor contains a large, poorly conserved N-terminal insertion domain (NID) of cryptic function. To date, only two NID-bearing Rho factors from high G + C Actinobacteria have been thoroughly characterized. Both can trigger RDTT at promoter-proximal sites or with structurally constrained transcripts that are unsuitable for the archetypal, NID-less Rho factor of Escherichia coli (_EcRho). Here, we provide the first biochemical characterization of a NID-bearing Rho factor from a low G + C bacterium. We show that Bacteroides fragilis Rho (_BfRho) is a bona fide RNA-dependent NTPase motor able to unwind long RNA:DNA duplexes and to disrupt transcription complexes. The large NID (~40% of total mass) strongly increases _BfRho affinity for RNA, is strictly required for RDTT, but does not promote RDTT at promoter-proximal sites or with a structurally constrained transcript. Furthermore, the NID does not preclude modulation of RDTT by transcription factors NusA and NusG or by the Rho inhibitor bicyclomycin. Although the NID contains a prion-like Q/N-rich motif, it does not spontaneously trigger formation of β-amyloids. Thus, despite its unusually large RNA binding domain, _BfRho behaves more like the NID-less _EcRho than NID-bearing counterparts from high G + C Actinobacteria. Our data highlight the evolutionary plasticity of Rho's N-terminal region and illustrate how RDTT is adapted to distinct genomic contents.

Non-essential ribosomal proteins in bacteria and archaea identified using COGs

Ribosomal proteins (RPs) are highly conserved across the bacterial and archaeal domains. Although many RPs are essential for survival, genome analysis demonstrates the absence of some RP genes in many bacterial and archaeal genomes. Furthermore, global transposon mutagenesis and/or targeted deletion showed that elimination of some RP genes had only a moderate effect on the bacterial growth rate. Here, we systematically analyze the evolutionary conservation of RPs in prokaryotes by compiling the list of the ribosomal genes that are missing from one or more genomes in the recently updated version of the Clusters of Orthologous Genes (COG) database. Some of these absences occurred because the respective genes carried frameshifts, presumably, resulting from sequencing errors, while others were overlooked and not translated during genome annotation. Apart from these annotation errors, we identified multiple genuine losses of RP genes in a variety of bacteria and archaea. Some of these losses are clade-specific, whereas others occur in symbionts and parasites with dramatically reduced genomes. The lists of computationally and experimentally defined non-essential ribosomal genes show a substantial overlap, revealing a common trend in prokaryote ribosome evolution that could be linked to the architecture and assembly of the ribosomes. Thus, RPs that are located at the surface of the ribosome and/or are incorporated at a late stage of ribosome assembly are more likely to be non-essential and to be lost during microbial evolution, particularly, in the course of genome compaction.IMPORTANCEIn many prokaryote genomes, one or more ribosomal protein (RP) genes are missing. Analysis of 1,309 prokaryote genomes included in the COG database shows that only about half of the RPs are universally conserved in bacteria and archaea. In contrast, up to 16 other RPs are missing in some genomes, primarily, tiny (<1 Mb) genomes of host-associated bacteria and archaea. Ten universal and nine archaea-specific ribosomal proteins show clear patterns of lineage-specific gene loss. Most of the RPs that are frequently lost from bacterial genomes are located on the ribosome periphery and are non-essential in Escherichia coli and Bacillus subtilis These results reveal general trends and common constraints in the architecture and evolution of ribosomes in prokaryotes.

DEG 15, an update of the Database of Essential Genes that includes built-in analysis tools

Essential genes refer to genes that are required by an organism to survive under specific conditions. Studies of the minimal-gene-set for bacteria have elucidated fundamental cellular processes that sustain life. The past five years have seen a significant progress in identifying human essential genes, primarily due to the successful use of CRISPR/Cas9 in various types of human cells. DEG 15, a new release of the Database of Essential Genes (www.essentialgene.org), has provided major advancements, compared to DEG 10. Specifically, the number of eukaryotic essential genes has increased by more than fourfold, and that of prokaryotic ones has more than doubled. Of note, the human essential-gene number has increased by more than tenfold. Moreover, we have developed built-in analysis modules by which users can perform various analyses, such as essential-gene distributions between bacterial leading and lagging strands, sub-cellular localization distribution, enrichment analysis of gene ontology and KEGG pathways, and generation of Venn diagrams to compare and contrast gene sets between experiments. Additionally, the database offers customizable BLAST tools for performing species- and experiment-specific BLAST searches. Therefore, DEG comprehensively harbors updated human-curated essential-gene records among prokaryotes and eukaryotes with built-in tools to enhance essential-gene analysis.

A Computational Framework Based on Ensemble Deep Neural Networks for Essential Genes Identification

Essential genes contain key information of genomes that could be the key to a comprehensive understanding of life and evolution. Because of their importance, studies of essential genes have been considered a crucial problem in computational biology. Computational methods for identifying essential genes have become increasingly popular to reduce the cost and time-consumption of traditional experiments. A few models have addressed this problem, but performance is still not satisfactory because of high dimensional features and the use of traditional machine learning algorithms. Thus, there is a need to create a novel model to improve the predictive performance of this problem from DNA sequence features. This study took advantage of a natural language processing (NLP) model in learning biological sequences by treating them as natural language words. To learn the NLP features, a supervised learning model was consequentially employed by an ensemble deep neural network. Our proposed method could identify essential genes with sensitivity, specificity, accuracy, Matthews correlation coefficient (MCC), and area under the receiver operating characteristic curve (AUC) values of 60.2%, 84.6%, 76.3%, 0.449, and 0.814, respectively. The overall performance outperformed the single models without ensemble, as well as the state-of-the-art predictors on the same benchmark dataset. This indicated the effectiveness of the proposed method in determining essential genes, in particular, and other sequencing problems, in general.

Nanaerobic growth enables direct visualization of dynamic cellular processes in human gut symbionts

Mechanistic studies of anaerobic gut bacteria have been hindered by the lack of a fluorescent protein system to track and visualize proteins and dynamic cellular processes in actively growing bacteria. Although underappreciated, many gut "anaerobes" are able to respire using oxygen as the terminal electron acceptor. The oxygen continually released from gut epithelial cells creates an oxygen gradient from the mucus layer to the anaerobic lumen [L. Albenberg et al., Gastroenterology 147, 1055-1063.e8 (2014)], with oxygen available to bacteria growing at the mucus layer. Here, we show that Bacteroides species are metabolically and energetically robust and do not mount stress responses in the presence of 0.10 to 0.14% oxygen, defined as nanaerobic conditions [A. D. Baughn, M. H. Malamy, Nature 427, 441-444 (2004)]. Taking advantage of this metabolic capability, we show that nanaerobic growth provides sufficient oxygen for the maturation of oxygen-requiring fluorescent proteins in Bacteroides species. Type strains of four different Bacteroides species show bright GFP fluorescence when grown nanaerobically versus anaerobically. We compared four different red fluorescent proteins and found that mKate2 yields the highest red fluorescence intensity in our assay. We show that GFP-tagged proteins can be localized in nanaerobically growing bacteria. In addition, we used time-lapse fluorescence microscopy to image dynamic type VI secretion system processes in metabolically active Bacteroides fragilis The ability to visualize fluorescently labeled Bacteroides and fluorescently linked proteins in actively growing nanaerobic gut symbionts ushers in an age of imaging analyses not previously possible in these bacteria.

ePath: an online database towards comprehensive essential gene annotation for prokaryotes

Experimental techniques for identification of essential genes (EGs) in prokaryotes are usually expensive, time-consuming and sometimes unrealistic. Emerging in silico methods provide alternative methods for EG prediction, but often possess limitations including heavy computational requirements and lack of biological explanation. Here we propose a new computational algorithm for EG prediction in prokaryotes with an online database (ePath) for quick access to the EG prediction results of over 4,000 prokaryotes ( https://www.pubapps.vcu.edu/epath/ ). In ePath, gene essentiality is linked to biological functions annotated by KEGG Ortholog (KO). Two new scoring systems, namely, E_score and P_score, are proposed for each KO as the EG evaluation criteria. E_score represents appearance and essentiality of a given KO in existing experimental results of gene essentiality, while P_score denotes gene essentiality based on the principle that a gene is essential if it plays a role in genetic information processing, cell envelope maintenance or energy production. The new EG prediction algorithm shows prediction accuracy ranging from 75% to 91% based on validation from five new experimental studies on EG identification. Our overall goal with ePath is to provide a comprehensive and reliable reference for gene essentiality annotation, facilitating the study of those prokaryotes without experimentally derived gene essentiality information.

Comparative Analyses of Fecal Microbiota in European Mouflon (Ovis orientalis musimon) and Blue Sheep (Pseudois nayaur) Living at Low or High Altitudes

The gut microbiota is a complex and essential system organ that plays an integrative role in balancing key vital functions in the host. Knowledge of the impact of altitude on the gut microbiota of European mouflon (Ovis orientalis musimon) and blue sheep (Pseudois nayaur) is currently limited. In this study, we compared the characteristics of gut microbiota in 5 mouflon at low altitude (K group), 4 mouflon at high altitude (L group), 4 blue sheep at low altitude (M group), and 4 blue sheep at high altitude (N group). The V3–V4 region of the 16S rRNA gene was analyzed using high-throughput sequencing. Analyses based on the operational taxonomic units showed significant changes in the gut microbial communities between groups at different altitudes. At the phylum level, groups at the high altitudes had a higher relative abundance of Firmicutes and a lower relative abundance of Bacteroidetes than those at the low altitudes. A higher Firmicutes:Bacteroidetes ratio is beneficial to animals in terms of the gut microbiota-mediated energy harvest. The relative abundance of Proteobacteria was significantly higher in the gut microbiota of mouflon sheep at high altitudes. At the genus level, the Bacteroides:Prevotella ratio was significantly higher in the low-altitude group (than the high-altitude group) of mouflon sheep and the ratio was significantly higher in the high-altitude group (than the low-altitude group) in blue sheep. In addition, the Ruminococcaceae_UCG-005 related to cellulose and starch digestion was the predominant genus in blue sheep and the relative abundance of the genus was significant higher in the high-altitude group than the low-altitude group of blue sheep (P < 0.01). In conclusion, our results suggested that the gut microbiota of high-altitude groups of sheep had stronger abilities related to energy metabolism and the decomposition of substances, e.g., fiber and cellulose, and that such abilities are associated with high-altitude adaptation.

The bare necessities: Uncovering essential and condition-critical genes with transposon sequencing

Querying gene function in bacteria has been greatly accelerated by the advent of transposon sequencing (Tn-seq) technologies (related Tn-seq strategies are known as TraDIS, INSeq, RB-TnSeq, and HITS). Pooled populations of transposon mutants are cultured in an environment and next-generation sequencing tools are used to determine areas of the genome that are important for bacterial fitness. In this review we provide an overview of Tn-seq methodologies and discuss how Tn-seq has been applied, or could be applied, to the study of oral microbiology. These applications include studying the essential genome as a means to rationally design therapeutic agents. Tn-seq has also contributed to our understanding of well-studied biological processes in oral bacteria. Other important applications include in vivo pathogenesis studies and use of Tn-seq to probe the molecular basis of microbial interactions. We also highlight recent advancements in techniques that act in synergy with Tn-seq such as clustered regularly interspaced short palindromic repeats (CRISPR) interference and microfluidic chip platforms.

Transposon Mutagenesis of Bacteroides fragilis

Bacteroides fragilis is Gram-negative obligatory anaerobe which usually resides in the gut of humans and animals. As an important member of the human gut microbiota it plays a vital role in digestion and absorption of nutrients as well as shaping of host immune system. B. fragilis is also infamous for causing serious infections. Treatment of B. fragilis infections caused emergence of multidrug-resistant strains. Molecular biology tools such as transposon mutagenesis help to decipher and understand commensal and pathogenic faces of B. fragilis. Using two mariner transposon vectors we describe the detailed methodology for the transposon mutagenesis of B. fragilis. We also describe two methods for the identification of transposon integration site (TIS) in transposon mutants. Transposon mutagenesis methods described in this chapter serve as a great tool for studying B. fragilis.

Comprehensive review of the identification of essential genes using computational methods: focusing on feature implementation and assessment

Essential genes have attracted increasing attention in recent years due to the important functions of these genes in organisms. Among the methods used to identify the essential genes, accurate and efficient computational methods can make up for the deficiencies of expensive and time-consuming experimental technologies. In this review, we have collected researches on essential gene predictions in prokaryotes and eukaryotes and summarized the five predominant types of features used in these studies. The five types of features include evolutionary conservation, domain information, network topology, sequence component and expression level. We have described how to implement the useful forms of these features and evaluated their performance based on the data of Escherichia coli MG1655, Bacillus subtilis 168 and human. The prerequisite and applicable range of these features is described. In addition, we have investigated the techniques used to weight features in various models. To facilitate researchers in the field, two available online tools, which are accessible for free and can be directly used to predict gene essentiality in prokaryotes and humans, were referred. This article provides a simple guide for the identification of essential genes in prokaryotes and eukaryotes.

The essential genome of the crenarchaeal model Sulfolobus islandicus

Sulfolobus islandicus is a model microorganism in the TACK superphylum of the Archaea, a key lineage in the evolutionary history of cells. Here we report a genome-wide identification of the repertoire of genes essential to S. islandicus growth in culture. We confirm previous targeted gene knockouts, uncover the non-essentiality of functions assumed to be essential to the Sulfolobus cell, including the proteinaceous S-layer, and highlight essential genes whose functions are yet to be determined. Phyletic distributions illustrate the potential transitions that may have occurred during the evolution of this archaeal microorganism, and highlight sets of genes that may have been associated with each transition. We use this comparative context as a lens to focus future research on archaea-specific uncharacterized essential genes that may provide valuable insights into the evolutionary history of cells.

Sulfolobus islandicus is a model organism within the TACK superphylum of the Archaea. Here, the authors perform a genome-wide analysis of essential genes in this organism, show that the proteinaceous S-layer is not essential, and explore potential stages of evolution of the essential gene repertoire in Archaea.

Metabolic models and gene essentiality data reveal essential and conserved metabolism in prokaryotes

Essential metabolic reactions are shaping constituents of metabolic networks, enabling viable and distinct phenotypes across diverse life forms. Here we analyse and compare modelling predictions of essential metabolic functions with experimental data and thereby identify core metabolic pathways in prokaryotes. Simulations of 15 manually curated genome-scale metabolic models were integrated with 36 large-scale gene essentiality datasets encompassing a wide variety of species of bacteria and archaea. Conservation of metabolic genes was estimated by analysing 79 representative genomes from all the branches of the prokaryotic tree of life. We find that essentiality patterns reflect phylogenetic relations both for modelling and experimental data, which correlate highly at the pathway level. Genes that are essential for several species tend to be highly conserved as opposed to non-essential genes which may be conserved or not. The tRNA-charging module is highlighted as ancestral and with high centrality in the networks, followed closely by cofactor metabolism, pointing to an early information processing system supplied by organic cofactors. The results, which point to model improvements and also indicate faults in the experimental data, should be relevant to the study of centrality in metabolic networks and ancient metabolism but also to metabolic engineering with prokaryotes.

If we tried to list every known chemical reaction within an organism–human, plant or even bacteria–we would get quite a long and confusing read. But when this information is represented in so-called genome-scale metabolic networks, we have the means to access computationally each of those reactions and their interconnections. Some parts of the network have alternatives, while others are unique and therefore can be essential for growth. Here, we simulate growth and compare essential reactions and genes for the simplest type of unicellular species–prokaryotes–to understand which parts of their metabolism are universally essential and potentially ancestral. We show that similar patterns of essential reactions echo phylogenetic relationships (this makes sense, as the genome provides the building plan for the enzymes that perform those reactions). Our computational predictions correlate strongly with experimental essentiality data. Finally, we show that a crucial step of protein synthesis (tRNA charging) and the synthesis and transformation of small molecules that enzymes require (cofactors) are the most essential and conserved parts of metabolism in prokaryotes. Our results are a step further in understanding the biology and evolution of prokaryotes but can also be relevant in applied studies including metabolic engineering and antibiotic design.

Mechanisms of Bacteroides fragilis resistance to metronidazole

Metronidazole-resistant Bacteroides fragilis (B. fragilis) have been reported worldwide. Several mechanisms contribute to B. fragilis resistance to metronidazole. In some cases, the mechanisms of metronidazole resistance are unknown. Understanding the mechanisms of resistance is important for therapy, the design of new alternative drugs, and control of resistant strains. In this study, a comprehensive review of the B. fragilis resistance mechanisms to metronidazole was prepared. The rate of metronidazole-resistant B. fragilis has been reported as ranging from 0.5% to 7.8% in many surveys. According to CLSI, isolates with MICs ≥32 μg/mL are considered to be metronidazole-resistant. In the majority of cases, metronidazole resistance in B. fragilis is coupled with the existence of nim genes. Metronidazole resistance could be induced in nim-negative strains by exposure to sub-MIC levels of metronidazole. There are multi-drug efflux pumps in B. fragilis which can pump out a variety of substrates such as metronidazole. The recA overexpression and deficiency of feoAB are other reported metronidazole resistance mechanisms in this bacterium.

A Two-Component System Regulates Bacteroides fragilis Toxin to Maintain Intestinal Homeostasis and Prevent Lethal Disease

Intestinal microbes are recognized for their role in human disease. Enterotoxigenic Bacteroides fragilis (ETBF) has been implicated in inflammatory bowel disease and colorectal cancer; however, colonization alone is insufficient to cause these illnesses. We hypothesized that homeostasis in healthy carriers is maintained by colonic mucus, the major constituent of which is the glycoprotein Muc2. We found that Muc2-deficient mice succumb to lethal disease from ETBF colonization in a B. fragilis toxin (BFT)-dependent manner. We identify a toxin regulator, the two-component system RprXY, which suppresses BFT expression in vitro and in vivo. Overexpression of either component was sufficient to prevent lethal disease in Muc2-deficient mice. Our studies demonstrate that homeostasis in the context of ETBF colonization is dependent on a dynamic interaction between intestinal mucus, a bacterial toxin, and a toxin regulatory system. Regulation of virulence may offer a therapeutic target to maintain intestinal homeostasis in susceptible patients.

Transposon Insertion Site Sequencing (TIS-Seq): An Efficient and High-Throughput Method for Determining Transposon Insertion Site(s) and Their Relative Abundances in a PiggyBac Transposon Mutant Pool by Next-Generation Sequencing

The PiggyBac (PB) transposon has emerged as a novel mutagenesis tool for understanding gene function and for phenotypic screening in eukaryotes. Successful screening of PB transposon mutants relies on efficient identification of transposon insertion site(s) (TIS) in mutant cells. However, currently available methods suffer from time-consuming steps. Here, we present the method for transposon insertion site sequencing (TIS-Seq) for high-throughput identification of TIS in transposon mutants. TIS-Seq provides qualitative and quantitative information on mutants present in a given PB transposon mutant library. TIS-Seq also facilitates identification of TIS in up to 96 individual/hand-picked mutants in a single MiniSeq/MiSeq run. TIS-Seq is a versatile method that can be easily modified to identify TIS from any kind of transposon mutant, as long as one end of the DNA sequence is known. Therefore, TIS-Seq is a promising method for transposon mutant screening. © 2017 by John Wiley & Sons, Inc.

Illumina Sequencing Approach to Characterize Thiamine Metabolism Related Bacteria and the Impacts of Thiamine Supplementation on Ruminal Microbiota in Dairy Cows Fed High-Grain Diets

The requirements of thiamine in adult ruminants are mainly met by ruminal bacterial synthesis, and thiamine deficiencies will occur when dairy cows overfed with high grain diet. However, there is limited knowledge with regard to the ruminal thiamine synthesis bacteria, and whether thiamine deficiency is related to the altered bacterial community by high grain diet is still unclear. To explore thiamine synthesis bacteria and the response of ruminal microbiota to high grain feeding and thiamine supplementation, six rumen-cannulated Holstein cows were randomly assigned into a replicated 3 × 3 Latin square design trial. Three treatments were control diet (CON, 20% dietary starch, DM basis), high grain diet (HG, 33.2% dietary starch, DM basis) and high grain diet supplemented with 180 mg thiamine/kg DMI (HG+T). On day 21 of each period, rumen content samples were collected at 3 h postfeeding. Ruminal thiamine concentration was detected by high performance liquid chromatography. The microbiota composition was determined using Illumina MiSeq sequencing of 16S rRNA gene. Cows receiving thiamine supplementation had greater ruminal pH value, acetate and thiamine content in the rumen. Principal coordinate analysis and similarity analysis indicated that HG feeding and thiamine supplementation caused a strong shift in bacterial composition and structure in the rumen. At the genus level, compared with CON group, the relative abundances of 19 genera were significantly changed by HG feeding. Thiamine supplementation increased the abundance of cellulolytic bacteria including Bacteroides, Ruminococcus 1, Pyramidobacter, Succinivibrio, and Ruminobacter, and their increases enhanced the fiber degradation and ruminal acetate production in HG+T group. Christensenellaceae R7, Lachnospira, Succiniclasticum, and Ruminococcaceae NK4A214 exhibited a negative response to thiamine supplementation. Moreover, correlation analysis revealed that ruminal thiamine concentration was positively correlated with Bacteroides, Ruminococcus 1, Ruminobacter, Pyramidobacter, and Fibrobacter. Taken together, we concluded that Bacteroides, Ruminococcus 1, Ruminobacter, Pyramidobacter, and Fibrobacter in rumen content may be associated with thiamine synthesis or thiamine is required for their growth and metabolism. In addition, thiamine supplementation can potentially improve rumen function, as indicated by greater numbers of cellulolytic bacteria within the rumen. These findings facilitate understanding of bacterial thiamine synthesis within rumen and thiamine's function in dairy cows.

The essential genomic landscape of the commensal Bifidobacterium breve UCC2003

Bifidobacteria are common gut commensals with purported health-promoting effects. This has encouraged scientific research into bifidobacteria, though recalcitrance to genetic manipulation and scarcity of molecular tools has hampered our knowledge on the precise molecular determinants of their health-promoting attributes and gut adaptation. To overcome this problem and facilitate functional genomic analyses in bifidobacteria, we created a large Tn5 transposon mutant library of the commensal Bifidobacterium breve UCC2003 that was further characterized by means of a Transposon Directed Insertion Sequencing (TraDIS) approach. Statistical analysis of transposon insertion distribution revealed a set of 453 genes that are essential for or markedly contribute to growth of this strain under laboratory conditions. These essential genes encode functions involved in the so-called bifid-shunt, most enzymes related to nucleotide biosynthesis and a range of housekeeping functions. Comparison to the Bifidobacterium and B. breve core genomes highlights a high degree of conservation of essential genes at the species and genus level, while comparison to essential gene datasets from other gut bacteria identified essential genes that appear specific to bifidobacteria. This work establishes a useful molecular tool for scientific discovery of bifidobacteria and identifies targets for further studies aimed at characterizing essential functions not previously examined in bifidobacteria.

The Suf Iron-Sulfur Cluster Biosynthetic System Is Essential in Staphylococcus aureus, and Decreased Suf Function Results in Global Metabolic Defects and Reduced Survival in Human Neutrophils

Staphylococcus aureus remains a causative agent for morbidity and mortality worldwide. This is in part a result of antimicrobial resistance, highlighting the need to uncover novel antibiotic targets and to discover new therapeutic agents. In the present study, we explored the possibility that iron-sulfur (Fe-S) cluster synthesis is a viable antimicrobial target. RNA interference studies established that Suf (sulfur mobilization)-dependent Fe-S cluster synthesis is essential in S. aureus We found that sufCDSUB were cotranscribed and that suf transcription was positively influenced by sigma factor B. We characterized an S. aureus strain that contained a transposon inserted in the intergenic space between sufC and sufD (sufD*), resulting in decreased transcription of sufSUB Consistent with the transcriptional data, the sufD* strain had multiple phenotypes associated with impaired Fe-S protein maturation. They included decreased activities of Fe-S cluster-dependent enzymes, decreased growth in media lacking metabolites that require Fe-S proteins for synthesis, and decreased flux through the tricarboxylic acid (TCA) cycle. Decreased Fe-S cluster synthesis resulted in sensitivity to reactive oxygen and reactive nitrogen species, as well as increased DNA damage and impaired DNA repair. The sufD* strain also exhibited perturbed intracellular nonchelated Fe pools. Importantly, the sufD* strain did not exhibit altered exoprotein production or altered biofilm formation, but it was attenuated for survival upon challenge by human polymorphonuclear leukocytes. The results presented are consistent with the hypothesis that Fe-S cluster synthesis is a viable target for antimicrobial development.

Exploratory Investigation of Bacteroides fragilis Transcriptional Response during In vitro Exposure to Subinhibitory Concentration of Metronidazole

Bacteroides fragilis, member from commensal gut microbiota, is an important pathogen associated to endogenous infections and metronidazole remains a valuable antibiotic for the treatment of these infections, although bacterial resistance is widely reported. Considering the need of a better understanding on the global mechanisms by which B. fragilis survive upon metronidazole exposure, we performed a RNA-seq transcriptomic approach with validation of gene expression results by qPCR. Bacteria strains were selected after in vitro subcultures with subinhibitory concentration (SIC) of the drug. From a wild type B. fragilis ATCC 43859 four derivative strains were selected: first and fourth subcultures under metronidazole exposure and first and fourth subcultures after drug removal. According to global gene expression analysis, 2,146 protein coding genes were identified, of which a total of 1,618 (77%) were assigned to a Gene Ontology term (GO), indicating that most known cellular functions were taken. Among these 2,146 protein coding genes, 377 were shared among all strains, suggesting that they are critical for B. fragilis survival. In order to identify distinct expression patterns, we also performed a K-means clustering analysis set to 15 groups. This analysis allowed us to detect the major activated or repressed genes encoding for enzymes which act in several metabolic pathways involved in metronidazole response such as drug activation, defense mechanisms against superoxide ions, high expression level of multidrug efflux pumps, and DNA repair. The strains collected after metronidazole removal were functionally more similar to those cultured under drug pressure, reinforcing that drug-exposure lead to drastic persistent changes in the B. fragilis gene expression patterns. These results may help to elucidate B. fragilis response during metronidazole exposure, mainly at SIC, contributing with information about bacterial survival strategies under stress conditions in their environment.

An Approach for Predicting Essential Genes Using Multiple Homology Mapping and Machine Learning Algorithms

Investigation of essential genes is significant to comprehend the minimal gene sets of cell and discover potential drug targets. In this study, a novel approach based on multiple homology mapping and machine learning method was introduced to predict essential genes. We focused on 25 bacteria which have characterized essential genes. The predictions yielded the highest area under receiver operating characteristic (ROC) curve (AUC) of 0.9716 through tenfold cross-validation test. Proper features were utilized to construct models to make predictions in distantly related bacteria. The accuracy of predictions was evaluated via the consistency of predictions and known essential genes of target species. The highest AUC of 0.9552 and average AUC of 0.8314 were achieved when making predictions across organisms. An independent dataset from Synechococcus elongatus, which was released recently, was obtained for further assessment of the performance of our model. The AUC score of predictions is 0.7855, which is higher than other methods. This research presents that features obtained by homology mapping uniquely can achieve quite great or even better results than those integrated features. Meanwhile, the work indicates that machine learning-based method can assign more efficient weight coefficients than using empirical formula based on biological knowledge.

Novel heterologous bacterial system reveals enhanced susceptibility to DNA damage mediated by yqgF, a nearly ubiquitous and often essential gene

Despite its presence in most bacteria, yqgF remains one of only 13 essential genes of unknown function in Escherichia coli. Predictions of YqgF function often derive from sequence similarity to RuvC, the canonical Holliday junction resolvase. To clarify its role, we deleted yqgF from a bacterium where it is not essential, Acinetobacter baylyi ADP1. Loss of yqgF impaired growth and increased the frequency of transformation and allelic replacement (TAR). When E. coli yqgF was inserted in place of its A. baylyi chromosomal orthologue, wild-type growth and TAR were restored. Functional similarities of yqgF in both gamma-proteobacteria were further supported by defective 16S rRNA processing by the A. baylyi mutant, an effect previously shown in E. coli for a temperature-sensitive yqgF allele. However, our data question the validity of deducing YqgF function strictly by comparison to RuvC. A. baylyi studies indicated that YqgF and RuvC can function in opposition to one another. Relative to the wild type, the ΔyqgF mutant had increased TAR frequency and increased resistance to nalidixic acid, a DNA-damaging agent. In contrast, deletion of ruvC decreased TAR frequency and lowered resistance to nalidixic acid. YqgF, but not RuvC, appears to increase bacterial susceptibility to DNA damage, including UV radiation. Nevertheless, the effects of yqgF on growth and TAR frequency were found to depend on amino acids analogous to catalytically required residues of RuvC. This new heterologous system should facilitate future yqgF investigation by exploiting the viability of A. baylyi yqgF mutants. In addition, bioinformatic analysis showed that a non-essential gene immediately upstream of yqgF in A. baylyi and E. coli (yqgE) is similarly positioned in most gamma- and beta-proteobacteria. A small overlap in the coding sequences of these adjacent genes is typical. This conserved genetic arrangement raises the possibility of a functional partnership between yqgE and yqgF.

Uncovering major genomic features of essential genes in Bacteria and a methanogenic Archaea

Identification of essential genes is critical to understanding the physiology of a species, proposing novel drug targets and uncovering minimal gene sets required for life. Although essential gene sets of several organisms have been determined using large-scale mutagenesis techniques, systematic studies addressing their conservation, genomic context and functions remain scant. Here we integrate 17 essential gene sets from genome-wide in vitro screenings and three gene collections required for growth in vivo, encompassing 15 Bacteria and one Archaea. We refine and generalize important theories proposed using Escherichia coli. Essential genes are typically monogenic and more conserved than nonessential genes. Genes required in vivo are less conserved than those essential in vitro, suggesting that more divergent strategies are deployed when the organism is stressed by the host immune system and unstable nutrient availability. We identified essential analogous pathways that would probably be missed by orthology-based essentiality prediction strategies. For example, Streptococcus sanguinis carries horizontally transferred isoprenoid biosynthesis genes that are widespread in Archaea. Genes specifically essential in Mycobacterium tuberculosis and Burkholderia pseudomallei are reported as potential drug targets. Moreover, essential genes are not only preferentially located in operons, but also occupy the first position therein, supporting the influence of their regulatory regions in driving transcription of whole operons. Finally, these important genomic features are shared between Bacteria and at least one Archaea, suggesting that high order properties of gene essentiality and genome architecture were probably present in the last universal common ancestor or evolved independently in the prokaryotic domains.

Modeling, molecular dynamics, and docking assessment of transcription factor rho: a potential drug target in Brucella melitensis 16M

The zoonotic disease brucellosis, a chronic condition in humans affecting renal and cardiac systems and causing osteoarthritis, is caused by Brucella, a genus of Gram-negative, facultative, intracellular pathogens. The mode of transmission and the virulence of the pathogens are still enigmatic. Transcription regulatory elements, such as rho proteins, play an important role in the termination of transcription and/or the selection of genes in Brucella. Adverse effects of the transcription inhibitors play a key role in the non-successive transcription challenges faced by the pathogens. In the investigation presented here, we computationally predicted the transcription termination factor rho (TtFRho) inhibitors against Brucella melitensis 16M via a structure-based method. In view the unknown nature of its crystal structure, we constructed a robust three-dimensional homology model of TtFRho’s structure by comparative modeling with the crystal structure of the Escherichia coli TtFRho (Protein Data Bank ID: 1PVO) as a template in MODELLER (v 9.10). The modeled structure was optimized by applying a molecular dynamics simulation for 2 ns with the CHARMM (Chemistry at HARvard Macromolecular Mechanics) 27 force field in NAMD (NAnoscale Molecular Dynamics program; v 2.9) and then evaluated by calculating the stereochemical quality of the protein. The flexible docking for the interaction phenomenon of the template consists of ligand-related inhibitor molecules from the ZINC (ZINC Is Not Commercial) database using a structure-based virtual screening strategy against minimized TtFRho. Docking simulations revealed two inhibitors compounds – ZINC24934545 and ZINC72319544 – that showed high binding affinity among 2,829 drug analogs that bind with key active-site residues; these residues are considered for protein-ligand binding and unbinding pathways via steered molecular dynamics simulations. Arg215 in the model plays an important role in the stability of the protein-ligand complex via a hydrogen bonding interaction by aromatic-π contacts, and the ADMET (absorption, distribution, metabolism, and excretion) analysis of best leads indicate nontoxic in nature with good potential for drug development.