Analytical tools and databases for metagenomics in the next-generation sequencing era

Metagenomic approaches and opportunities in arid soil research

Arid soils present unique challenges and opportunities for studying microbial diversity and bioactive potential due to the extreme environmental conditions they bear. This review article investigates soil metagenomics as an emerging tool to explore complex microbial dynamics and unexplored bioactive potential in harsh environments. Utilizing advanced metagenomic techniques, diverse microbial populations that grow under extreme conditions such as high temperatures, salinity, high pH levels, and exposure to metals and radiation can be studied. The use of extremophiles to discover novel natural products and biocatalysts emphasizes the role of functional metagenomics in identifying enzymes and secondary metabolites for industrial and pharmaceutical purposes. Metagenomic sequencing uncovers a complex network of microbial diversity, offering significant potential for discovering new bioactive compounds. Functional metagenomics, connecting taxonomic diversity to genetic capabilities, provides a pathway to identify microbes' mechanisms to synthesize valuable secondary metabolites and other bioactive substances. Contrary to the common perception of desert soil as barren land, the metagenomic analysis reveals a rich diversity of life forms adept at extreme survival. It provides valuable findings into their resilience and potential applications in biotechnology. Moreover, the challenges associated with metagenomics in arid soils, such as low microbial biomass, high DNA degradation rates, and DNA extraction inhibitors and strategies to overcome these issues, outline the latest advancements in extraction methods, high-throughput sequencing, and bioinformatics. The importance of metagenomics for investigating diverse environments opens the way for future research to develop sustainable solutions in agriculture, industry, and medicine. Extensive studies are necessary to utilize the full potential of these powerful microbial communities. This research will significantly improve our understanding of microbial ecology and biotechnology in arid environments.

The Rising Role of Omics and Meta-Omics in Table Olive Research

Table olives are often the result of fermentation, a process where microorganisms transform raw materials into the final product. The microbial community can significantly impact the organoleptic characteristics and safety of table olives, and it is influenced by various factors, including the processing methods. Traditional culture-dependent techniques capture only a fraction of table olives' intricate microbiota, prompting a shift toward culture-independent methods to address this knowledge gap. This review explores recent advances in table olive research through omics and meta-omics approaches. Genomic analysis of microorganisms isolated from table olives has revealed multiple genes linked to technological and probiotic attributes. An increasing number of studies concern metagenomics and metabolomics analyses of table olives. The former offers comprehensive insights into microbial diversity and function, while the latter identifies aroma and flavor determinants. Although proteomics and transcriptomics studies remain limited in the field, they have the potential to reveal deeper layers of table olives' microbiome composition and functionality. Despite the challenges associated with implementing multi-omics approaches, such as the reliance on advanced bioinformatics tools and computational resources, they hold the promise of groundbreaking advances in table olive processing technology.

Integrated multi-omics analyses of microbial communities: a review of the current state and future directions

Integrated multi-omics analyses of microbiomes have become increasingly common in recent years as the emerging omics technologies provide an unprecedented opportunity to better understand the structural and functional properties of microbial communities. Consequently, there is a growing need for and interest in the concepts, approaches, considerations, and available tools for investigating diverse environmental and host-associated microbial communities in an integrative manner. In this review, we first provide a general overview of each omics analysis type, including a brief history, typical workflow, primary applications, strengths, and limitations. Then, we inform on both experimental design and bioinformatics analysis considerations in integrated multi-omics analyses, elaborate on the current approaches and commonly used tools, and highlight the current challenges. Finally, we discuss the expected key advances, emerging trends, potential implications on various fields from human health to biotechnology, and future directions.

Bacterial diversity in the aquatic system in India based on metagenome analysis-a critical review

Microbial analysis has become one of the most critical areas in aquatic ecology and a crucial component for assessing the contribution of microbes in food web dynamics and biogeochemical processes. Initial research was focused on estimating the abundance and distribution of the microbes using microscopy and culture-based analysis, which are undoubtedly complex tasks. Over the past few decades, microbiologists have endeavored to apply and extend molecular techniques to address pertinent questions related to the function and metabolism of microbes in aquatic ecology. Metagenomics analysis has revolutionized aquatic ecology studies involving the investigation of the genome of a mixed community of organisms in an ecosystem to identify microorganisms, their functionality, and the discovery of novel proteins. This review discusses the metagenomics analysis of bacterial diversity in and around different aquatic systems in India.

Combining omics tools for the characterization of the microbiota of diverse vinegars obtained by submerged culture: 16S rRNA amplicon sequencing and MALDI-TOF MS

Vinegars elaborated in southern Spain are highly valued all over the world because of their exceptional organoleptic properties and high quality. Among the factors which influence the characteristics of the final industrial products, the composition of the microbiota responsible for the process and the raw material used as acetification substrate have a crucial role. The current state of knowledge shows that few microbial groups are usually present throughout acetification, mainly acetic acid bacteria (AAB), although other microorganisms, present in smaller proportions, may also affect the overall activity and behavior of the microbial community. In the present work, the composition of a starter microbiota propagated on and subsequently developing three acetification profiles on different raw materials, an alcohol wine medium and two other natural substrates (a craft beer and fine wine), was characterized and compared. For this purpose, two different "omics" tools were combined for the first time to study submerged vinegar production: 16S rRNA amplicon sequencing, a culture-independent technique, and matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS), a culture-dependent method. Analysis of the metagenome revealed numerous taxa from 30 different phyla and highlighted the importance of the AAB genus Komagataeibacter, which was much more frequent than the other taxa, and Acetobacter; interestingly, also archaea from the Nitrososphaeraceae family were detected by 16S rRNA amplicon sequencing. MALDI-TOF MS confirmed the presence of Komagataeibacter by the identification of K. intermedius. These tools allowed for identifying some taxonomic groups such as the bacteria genera Cetobacterium and Rhodobacter, the bacteria species Lysinibacillus fusiformis, and even archaea, never to date found in this medium. Definitely, the effect of the combination of these techniques has allowed first, to confirm the composition of the predominant microbiota obtained in our previous metaproteomics approaches; second, to identify the microbial community and discriminate specific species that can be cultivated under laboratory conditions; and third, to obtain new insights on the characterization of the acetification raw materials used. These first findings may contribute to improving the understanding of the microbial communities' role in the vinegar-making industry.

Metagenomics Next Generation Sequencing (mNGS): An Exciting Tool for Early and Accurate Diagnostic of Fungal Pathogens in Plants

Crop output is directly impacted by infections, with fungi as the major plant pathogens, making accurate diagnosis of these threats crucial. Developing technology and multidisciplinary approaches are turning to genomic analyses in addition to traditional culture methods in diagnostics of fungal plant pathogens. The metagenomic next-generation sequencing (mNGS) method is preferred for genotyping identification of organisms, identification at the species level, illumination of metabolic pathways, and determination of microbiota. Moreover, the data obtained so far show that this new approach is promising as an emerging new trend in fungal disease detection. Another approach covered by mNGS technologies, known as metabarcoding, enables use of specific markers specific to a genetic region and allows for genotypic identification by facilitating the sequencing of certain regions. Although the core concept of mNGS remains constant across applications, the specific sequencing methods and bioinformatics tools used to analyze the data differ. In this review, we focus on how mNGS technology, including metabarcoding, is applied for detecting fungal pathogens and its promising developments for the future.

Extension of the shelf-life of fresh pasta using modified atmosphere packaging and bioprotective cultures

Microbial stability of fresh pasta depends on heat treatment, storage temperature, proper preservatives, and atmosphere packaging. This study aimed at improving the microbial quality, safety, and shelf life of fresh pasta using modified atmosphere composition and packaging with or without the addition of bioprotective cultures (Lactobacillus acidophilus, Lactobacillus casei, Bifidobacterium spp., and Bacillus coagulans) into semolina. Three fresh pasta variants were made using (i) the traditional protocol (control), MAP (20:80 CO₂:N₂), and barrier packaging, (ii) the experimental MAP (40:60 CO₂:N₂) and barrier packaging, and (iii) the experimental MAP, barrier packaging, and bioprotective cultures. Their effects on physicochemical properties (i.e., content on macro elements, water activity, headspace O₂, CO₂ concentrations, and mycotoxins), microbiological patterns, protein, and volatile organic compounds (VOC) were investigated at the beginning and the end of the actual or extended shelf-life through traditional and multi-omics approaches. We showed that the gas composition and properties of the packaging material tested in the experimental MAP system, with or without bioprotective cultures, positively affect features of fresh pasta avoiding changes in their main chemical properties, allowing for a storage longer than 120 days under refrigerated conditions. These results support that, although bioprotective cultures were not all able to grow in tested conditions, they can control the spoilage and the associated food-borne microbiota in fresh pasta during storage by their antimicrobials and/or fermentation products synergically. The VOC profiling, based on gas-chromatography mass-spectrometry (GC-MS), highlighted significant differences affected by the different manufacturing and packaging of samples. Therefore, the use of the proposed MAP system and the addition of bioprotective cultures can be considered an industrial helpful strategy to reduce the quality loss during refrigerated storage and to increase the shelf life of fresh pasta for additional 30 days by allowing the economic and environmental benefits spurring innovation in existing production models.

Oligotrophy vs. copiotrophy in an alkaline and saline habitat of Lonar Lake

We reported our comparative observations on oligotrophs vs. copiotrophs from a hyper-alkaline and hypersaline habitat, Lonar Lake, situated in the Buldhana district of Maharashtra, India. Cell numbers of oligotrophic and copiotrophic microbes from the sediment were enumerated by the three-tube most probable number (MPN) method using an array of nutrient-rich and oligotrophic (≈10–20 mg carbon L−1) media offering simulated natural conditions of pH and salinity. A total of 50 strains from 15 different genera and 30 different species were isolated from the highest positive dilutions of MPN to identify the taxa of oligotrophs and copiotrophic microorganisms dominating in Lonar Lake. We did not get any true oligotrophs due to their adaptation to higher carbon levels during the isolation procedure. On the contrary, several true copiotrophs, which could not adapt and survive on a low-carbon medium, were isolated. It is also observed that changes in medium composition and nutrient level altered the selection of organisms from the same sample. Our data indicate that copiotrophic microorganisms dominate the eutrophic Lonar Lake, which is also supported by the past metagenomics studies from the same site. We also reported that quick depletion of carbon from oligotrophic medium worked as a limiting factor, inducing cell death after 2–3 generations and preventing the development of visible colonies on plates and sufficient optical density in liquid medium. Therefore, a long-term supply of low levels of carbon, followed by isolation on enriched media, can serve as a good strategy in isolation of novel taxa of microorganism, with industrial or environmental importance.

Recent Advances of Marine Sponge-Associated Microorganisms as a Source of Commercially Viable Natural Products

Many industrially significant compounds have been derived from natural products in the environment. Research efforts so far have contributed to the discovery of beneficial natural products that have improved the quality of life on Earth. As one of the sources of natural products, marine sponges have been progressively recognised as microbial hotspots with reports of the sponges harbouring diverse microbial assemblages, genetic material, and metabolites with multiple industrial applications. Therefore, this paper aims at reviewing the recent literature (primarily published between 2016 and 2022) on the types and functions of natural products synthesised by sponge-associated microorganisms, thereby helping to bridge the gap between research and industrial applications. The metabolites that have been derived from sponge-associated microorganisms, mostly bacteria, fungi, and algae, have shown application prospects especially in medicine, cosmeceutical, environmental protection, and manufacturing industries. Sponge bacteria-derived natural products with medical properties harboured anticancer, antibacterial, antifungal, and antiviral functions. Efforts in re-identifying the origin of known and future sponge-sourced natural products would further clarify the roles and significance of microbes within marine sponges.

Evaluating the Prevalence of Foodborne Pathogens in Livestock Using Metagenomics Approach

Food safety is the most important global health issue due to foodborne pathogens after consumption of contaminated food. Foodborne bacteria such as Escherichia coli, Salmonella enterica, Staphylococcus aureus, Campylobacter spp., Bacillus cereus, Vibrio spp., Yersinia enterocolitica and Clostridium perfringens are leading causes of the majority of foodborne illnesses and deaths. These foodborne pathogens often come from the livestock feces, thus, we analyzed fecal microbial communities of three different livestock species to investigate the prevalence of foodborne pathogens in livestock feces using metagenomics analysis. Our data showed that alpha diversities of microbial communities were different according to livestock species. The microbial diversity of cattle feces was higher than that of chicken or pig feces. Moreover, microbial communities were significantly different among these three livestock species (cattle, chicken, and pig). At the genus level, Staphylococcus and Clostridium were found in all livestock feces, with chicken feces having higher relative abundances of Staphylococcus and Clostridium than cattle and pig feces. Genera Bacillus, Campylobacter, and Vibrio were detected in cattle feces. Chicken samples contained Bacillus, Listeria, and Salmonella with low relative abundance. Other genera such as Corynebacterium, Streptococcus, Neisseria, Helicobacter, Enterobacter, Klebsiella, and Pseudomonas known to be opportunistic pathogens were also detected in cattle, chicken, and pig feces. Results of this study might be useful for controlling the spread of foodborne pathogens in farm environments known to provide natural sources of these microorganisms.

The endophytome (plant-associated microbiome): methodological approaches, biological aspects, and biotech applications

Similar to other organisms, plants establish interactions with a variety of microorganisms in their natural environment. The plant microbiome occupies the host plant's tissues, either internally or on its surfaces, showing interactions that can assist in its growth, development, and adaptation to face environmental stresses. The advance of metagenomics and metatranscriptomics approaches has strongly driven the study and recognition of plant microbiome impacts. Research in this regard provides comprehensive information about the taxonomic and functional aspects of microbial plant communities, contributing to a better understanding of their dynamics. Evidence of the plant microbiome's functional potential has boosted its exploitation to develop more ecological and sustainable agricultural practices that impact human health. Although microbial inoculants' development and use are promising to revolutionize crop production, interdisciplinary studies are needed to identify new candidates and promote effective practical applications. On the other hand, there are challenges in understanding and analyzing complex data generated within a plant microbiome project's scope. This review presents aspects about the complex structuring and assembly of the microbiome in the host plant's tissues, metagenomics, and metatranscriptomics approaches for its understanding, covering descriptions of recent studies concerning metagenomics to characterize the microbiome of non-model plants under different aspects. Studies involving bio-inoculants, isolated from plant microbial communities, capable of assisting in crops' productivity, are also reviewed.

Current Methods, Common Practices, and Perspectives in Tracking and Monitoring Bioinoculants in Soil

Microorganisms promised to lead the bio-based revolution for a more sustainable agriculture. Beneficial microorganisms could be a valid alternative to the use of chemical fertilizers or pesticides. However, the increasing use of microbial inoculants is also raising several questions about their efficacy and their effects on the autochthonous soil microorganisms. There are two major issues on the application of bioinoculants to soil: (i) their detection in soil, and the analysis of their persistence and fate; (ii) the monitoring of the impact of the introduced bioinoculant on native soil microbial communities. This review explores the strategies and methods that can be applied to the detection of microbial inoculants and to soil monitoring. The discussion includes a comprehensive critical assessment of the available tools, based on morpho-phenological, molecular, and microscopic analyses. The prospects for future development of protocols for regulatory or commercial purposes are also discussed, underlining the need for a multi-method (polyphasic) approach to ensure the necessary level of discrimination required to track and monitor bioinoculants in soil.

Target classification in the 14th round of the critical assessment of protein structure prediction (CASP14)

An evolutionary-based definition and classification of target evaluation units (EUs) is presented for the 14th round of the critical assessment of structure prediction (CASP14). CASP14 targets included 84 experimental models submitted by various structural groups (designated T1024-T1101). Targets were split into EUs based on the domain organization of available templates and performance of server groups. Several targets required splitting (19 out of 25 multidomain targets) due in part to observed conformation changes. All in all, 96 CASP14 EUs were defined and assigned to tertiary structure assessment categories (Topology-based FM or High Accuracy-based TBM-easy and TBM-hard) considering their evolutionary relationship to existing ECOD fold space: 24 family level, 50 distant homologs (H-group), 12 analogs (X-group), and 10 new folds. Principal component analysis and heatmap visualization of sequence and structure similarity to known templates as well as performance of servers highlighted trends in CASP14 target difficulty. The assigned evolutionary levels (i.e., H-groups) and assessment classes (i.e., FM) displayed overlapping clusters of EUs. Many viral targets diverged considerably from their template homologs and thus were more difficult for prediction than other homology-related targets. On the other hand, some targets did not have sequence-identifiable templates, but were predicted better than expected due to relatively simple arrangements of secondary structural elements. An apparent improvement in overall server performance in CASP14 further complicated traditional classification, which ultimately assigned EUs into high-accuracy modeling (27 TBM-easy and 31 TBM-hard), topology (23 FM), or both (15 FM/TBM).

Comparison of Methods for Picking the Operational Taxonomic Units From Amplicon Sequences

With the advent of next-generation sequencing technology, it has become convenient and cost efficient to thoroughly characterize the microbial diversity and taxonomic composition in various environmental samples. Millions of sequencing data can be generated, and how to utilize this enormous sequence resource has become a critical concern for microbial ecologists. One particular challenge is the OTUs (operational taxonomic units) picking in 16S rRNA sequence analysis. Lucky, this challenge can be directly addressed by sequence clustering that attempts to group similar sequences. Therefore, numerous clustering methods have been proposed to help to cluster 16S rRNA sequences into OTUs. However, each method has its clustering mechanism, and different methods produce diverse outputs. Even a slight parameter change for the same method can also generate distinct results, and how to choose an appropriate method has become a challenge for inexperienced users. A lot of time and resources can be wasted in selecting clustering tools and analyzing the clustering results. In this study, we introduced the recent advance of clustering methods for OTUs picking, which mainly focus on three aspects: (i) the principles of existing clustering algorithms, (ii) benchmark dataset construction for OTU picking and evaluation metrics, and (iii) the performance of different methods with various distance thresholds on benchmark datasets. This paper aims to assist biological researchers to select the reasonable clustering methods for analyzing their collected sequences and help algorithm developers to design more efficient sequences clustering methods.

SeSaMe: Metagenome Sequence Classification of Arbuscular Mycorrhizal Fungi-associated Microorganisms

Arbuscular mycorrhizal fungi (AMF) are plant root symbionts that play key roles in plant growth and soil fertility. They are obligate biotrophic fungi that form coenocytic multinucleated hyphae and spores. Numerous studies have shown that diverse microorganisms live on the surface of and inside their mycelia, resulting in a metagenome when whole-genome sequencing (WGS) data are obtained from sequencing AMF cultivated in vivo. The metagenome contains not only the AMF sequences, but also those from associated microorganisms. In this study, we introduce a novel bioinformatics program, Spore-associated Symbiotic Microbes (SeSaMe), designed for taxonomic classification of short sequences obtained by next-generation DNA sequencing. A genus-specific usage bias database was created based on amino acid usage and codon usage of a three consecutive codon DNA 9-mer encoding an amino acid trimer in a protein secondary structure. The program distinguishes between coding sequence (CDS) and non-CDS, and classifies a query sequence into a genus group out of 54 genera used as reference. The mean percentages of correct predictions of the CDS and the non-CDS test sets at the genus level were 71% and 50% for bacteria, 68% and 73% for fungi (excluding AMF), and 49% and 72% for AMF (Rhizophagus irregularis), respectively. SeSaMe provides not only a means for estimating taxonomic diversity and abundance but also the gene reservoir of the reference taxonomic groups associated with AMF. Therefore, it enables users to study the symbiotic roles of associated microorganisms. It can also be applicable to other microorganisms as well as soil metagenomes. SeSaMe is freely available at www.fungalsesame.org.

Omics technologies for improved diagnosis and treatment of colorectal cancer: Technical advancement and major perspectives

Colorectal cancer (CRC) ranks third among the most commonly occurring cancers worldwide, and it causes half a million deaths annually. Alongside mechanistic study for CRC detection and treatment by conventional techniques, new technologies have been developed to study CRC. These technologies include genomics, transcriptomics, proteomics, and metabolomics which elucidate DNA markers, RNA transcripts, protein and, metabolites produced inside the colon and rectum part of the gut. All these approaches form the omics arena, which presents a remarkable opportunity for the discovery of novel prognostic, diagnostic and therapeutic biomarkers and also delineate the underlying mechanism of CRC causation, which may further help in devising treatment strategies. This review also mentions the latest developments in metagenomics and culturomics as emerging evidence suggests that metagenomics of gut microbiota has profound implications in the causation, prognosis, and treatment of CRC. A majority of bacteria cannot be studied as they remain unculturable, so culturomics has also been strengthened to develop culture conditions suitable for the growth of unculturable bacteria and identify unknown bacteria. The overall purpose of this review is to succinctly evaluate the application of omics technologies in colorectal cancer research for improving the diagnosis and treatment strategies.

HoSeIn: A Workflow for Integrating Various Homology Search Results from Metagenomic and Metatranscriptomic Sequence Datasets

Data generated by metagenomic and metatranscriptomic experiments is both enormous and inherently noisy. When using taxonomy-dependent alignment-based methods to classify and label reads, the first step consists in performing homology searches against sequence databases. To obtain the most information from the samples, nucleotide sequences are usually compared to various databases (nucleotide and protein) using local sequence aligners such as BLASTN and BLASTX. Nevertheless, the analysis and integration of these results can be problematic because the outputs from these searches usually show inconsistencies, which can be notorious when working with RNA-seq. Moreover, and to the best of our knowledge, existing tools do not criss-cross and integrate information from the different homology searches, but provide the results of each analysis separately. We developed the HoSeIn workflow to intersect the information from these homology searches, and then determine the taxonomic and functional profile of the sample using this integrated information. The workflow is based on the assumption that the sequences that correspond to a certain taxon are composed of: sequences that were assigned to the same taxon by both homology searches; sequences that were assigned to that taxon by one of the homology searches but returned no hits in the other one.

Evolution of an 8-week upper-division metagenomics course: Diagramming a learning path from observational to quantitative microbiome analysis

Metagenomics is a tool that enables researchers to study genetic material recovered directly from microbial communities or microbiomes. Fueled by advances in sequencing technologies, bioinformatics tools, and sample processing, metagenomics studies promise to expand our understanding of human health and the use of microorganisms for agriculture and industry. Therefore, teaching students about metagenomics is crucial to prepare them for modern careers in the life sciences. However, the increasing number of different approaches makes teaching metagenomics to students a challenge. This 8-week metagenomics laboratory course has the objective of introducing upper-level undergraduate and graduate students to strategies for designing, executing, and analyzing microbiome investigations. The laboratory component begins with sample processing, library preparation, and submission for high-throughput sequencing before transitioning to computer-based activities, which include an introduction to several fundamental computational metagenomics tools. Students analyze their sequencing results and deposit findings in sequence databases. The laboratory component is complemented by a weekly lecture, where active learning sessions promote retrieval practice and allow students to reflect on and diagram processes performed in the laboratory. Attainment of student learning outcomes was assessed through the completion of various course assignments: laboratory reports, presentations, and a cumulative final exam. Further, students' perceptions of their gains relevant to the learning outcomes were evaluated using pre- and postcourse surveys. Collectively, these data demonstrate that this course results in the attainment of the learning outcomes and that this approach provides an adaptable way to expose students to the cutting-edge field of metagenomics.

Human microbiome: an academic update on human body site specific surveillance and its possible role

Human body is inhabited by vast number of microorganisms which form a complex ecological community and influence the human physiology, in the aspect of both health and diseases. These microbes show a relationship with the human immune system based on coevolution and, therefore, have a tremendous potential to contribute to the metabolic function, protection against the pathogen and in providing nutrients and energy. However, of these microbes, many carry out some functions that play a crucial role in the host physiology and may even cause diseases. The introduction of new molecular technologies such as transcriptomics, metagenomics and metabolomics has contributed to the upliftment on the findings of the microbiome linked to the humans in the recent past. These rapidly developing technologies are boosting our capacity to understand about the human body-associated microbiome and its association with the human health. The highlights of this review are inclusion of how to derive microbiome data and the interaction between human and associated microbiome to provide an insight on the role played by the microbiome in biological processes of the human body as well as the development of major human diseases.

Diversity, Ecology, and Prevalence of Antimicrobials in Nature

Microorganisms possess a variety of survival mechanisms, including the production of antimicrobials that function to kill and/or inhibit the growth of competing microorganisms. Studies of antimicrobial production have largely been driven by the medical community in response to the rise in antibiotic-resistant microorganisms and have involved isolated pure cultures under artificial laboratory conditions neglecting the important ecological roles of these compounds. The search for new natural products has extended to biofilms, soil, oceans, coral reefs, and shallow coastal sediments; however, the marine deep subsurface biosphere may be an untapped repository for novel antimicrobial discovery. Uniquely, prokaryotic survival in energy-limited extreme environments force microbial populations to either adapt their metabolism to outcompete or produce novel antimicrobials that inhibit competition. For example, subsurface sediments could yield novel antimicrobial genes, while at the same time answering important ecological questions about the microbial community.

The effect of 16S rRNA region choice on bacterial community metabarcoding results

In this work, we compare the resolution of V2-V3 and V3-V4 16S rRNA regions for the purposes of estimating microbial community diversity using paired-end Illumina MiSeq reads, and show that the fragment, including V2 and V3 regions, has higher resolution for lower-rank taxa (genera and species). It allows for a more precise distance-based clustering of reads into species-level OTUs. Statistically convergent estimates of the diversity of major species (defined as those that together are covered by 95% of reads) can be achieved at the sample sizes of 10000 to 15000 reads. The relative error of the Shannon index estimate for this condition is lower than 4%.

Omics in traditional vegetable fermented foods and beverages

For a long time, food microbiota has been studied using traditional microbiological techniques. With the arrival of molecular or culture-independent techniques, a strong understanding of microbiota dynamics has been achieved. However, analyzing the functional role of microbial communities is not an easy task. The application of omics sciences to the study of fermented foods would provide the metabolic and functional understanding of the microbial communities and their impact on the fermented product, including the molecules that define its aroma and flavor, as well as its nutritional properties. Until now, most omics studies have focused on commercial fermented products, such as cheese, wine, bread and beer, but traditional fermented foods have been neglected. Therefore, the information that allows to relate the present microbiota in the food and its properties remains limited. In this review, reports on the applications of omics in the study of traditional fermented foods and beverages are reviewed to propose new ways to analyze the fermentation phenomena.

Genetic and functional diversity of double-stranded DNA viruses in a tropical monsoonal estuary, India

The present study illustrates the genetic diversity of four uncultured viral communities from the surface waters of Cochin Estuary (CE), India. Viral diversity inferred using Illumina HiSeq paired-end sequencing using a linker-amplified shotgun library (LASL) revealed different double-stranded DNA (dsDNA) viral communities. The water samples were collected from four stations PR1, PR2, PR3, and PR4, during the pre-monsoon (PRM) season. Analysis of virus families indicated that the Myoviridae was the most common viral community in the CE followed by Siphoviridae and Podoviridae. There were significant (p < 0.05) spatial variations in the relative abundance of dominant families in response to the salinity regimes. The relative abundance of Myoviridae and Podoviridae were high in the euryhaline region and Siphoviridae in the mesohaline region of the estuary. The predominant phage type in CE was phages that infected Synechococcus. The viral proteins were found to be involved in major functional activities such as ATP binding, DNA binding, and DNA replication. The study highlights the genetic diversity of dsDNA viral communities and their functional protein predictions from a highly productive estuarine system. Further, the metavirome data generated in this study will enhance the repertoire of publicly available dataset and advance our understanding of estuarine viral ecology.

NFATC3-PLA2G15 Fusion Transcript Identified by RNA Sequencing Promotes Tumor Invasion and Proliferation in Colorectal Cancer Cell Lines

Purpose

This study was designed to identify novel fusion transcripts (FTs) and their functional significance in colorectal cancer (CRC) lines.

Materials and Methods

We performed paired-end RNA sequencing of 28 CRC cell lines. FT candidates were identified using TopHat-fusion, ChimeraScan, and FusionMap tools and further experimental validation was conducted through reverse transcription-polymerase chain reaction and Sanger sequencing. FT was depleted in human CRC line and the effects on cell proliferation, cell migration, and cell invasion were analyzed.

Results

One thousand three hundred eighty FT candidates were detected through bioinformatics filtering. We selected six candidate FTs, including four inter-chromosomal and two intrachromosomal FTs and each FT was found in at least one of the 28 cell lines. Moreover, when we tested 19 pairs of CRC tumor and adjacent normal tissue samples, NFATC3–PLA2G15 FT was found in two. Knockdown of NFATC3–PLA2G15 using siRNA reduced mRNA expression of epithelial–mesenchymal transition (EMT) markers such as vimentin, twist, and fibronectin and increased mesenchymal–epithelial transition markers of E-cadherin, claudin-1, and FOXC2 in colo-320 cell line harboring NFATC3–PLA2G15 FT. The NFATC3–PLA2G15 knockdown also inhibited invasion, colony formation capacity, and cell proliferation.

Conclusion

These results suggest that that NFATC3–PLA2G15 FTs may contribute to tumor progression by enhancing invasion by EMT and proliferation.

Formal description of sequence-based voucherless Fungi: promises and pitfalls, and how to resolve them

There is urgent need for a formal nomenclature of sequence-based, voucherless Fungi, given that environmental sequencing has accumulated more than one billion fungal ITS reads in the Sequence Read Archive, about 1,000 times as many as fungal ITS sequences in GenBank. These unnamed Fungi could help to bridge the gap between 115,000 to 140,000 currently accepted and 2.2 to 3.8 million predicted species, a gap that cannot realistically be filled using specimen or culture-based inventories. The Code never aimed at placing restrictions on the nature of characters chosen for taxonomy, and the requirement for physical types is now becoming a constraint on the advancement of science. We elaborate on the promises and pitfalls of sequence-based nomenclature and provide potential solutions to major concerns of the mycological community. Types of sequence-based taxa, which by default lack a physical specimen or culture, could be designated in four alternative ways: (1) the underlying sample ('bag' type), (2) the DNA extract, (3) fluorescent in situ hybridization (FISH), or (4) the type sequence itself. Only (4) would require changes to the Code and the latter would be the most straightforward approach, complying with three of the five principal functions of types better than physical specimens. A fifth way, representation of the sequence in an illustration, has been ruled as unacceptable in the Code. Potential flaws in sequence data are analogous to flaws in physical types, and artifacts are manageable if a stringent analytical approach is applied. Conceptual errors such as homoplasy, intragenomic variation, gene duplication, hybridization, and horizontal gene transfer, apply to all molecular approaches and cannot be used as a specific argument against sequence-based nomenclature. The potential impact of these phenomena is manageable, as phylogenetic species delimitation has worked satisfactorily in Fungi. The most serious shortcoming of sequence-based nomenclature is the likelihood of parallel classifications, either by describing taxa that already have names based on physical types, or by using different markers to delimit species within the same lineage. The probability of inadvertently establishing sequence-based species that have names available is between 20.4 % and 1.5 % depending on the number of globally predicted fungal species. This compares favourably to a historical error rate of about 30 % based on physical types, and this rate could be reduced to practically zero by adding specific provisions to this approach in the Code. To avoid parallel classifications based on different markers, sequence-based nomenclature should be limited to a single marker, preferably the fungal ITS barcoding marker; this is possible since sequence-based nomenclature does not aim at accurate species delimitation but at naming lineages to generate a reference database, independent of whether these lineages represent species, closely related species complexes, or infraspecies. We argue that clustering methods are inappropriate for sequence-based nomenclature; this approach must instead use phylogenetic methods based on multiple alignments, combined with quantitative species recognition methods. We outline strategies to obtain higher-level phylogenies for ITS-based, voucherless species, including phylogenetic binning, 'hijacking' species delimitation methods, and temporal banding. We conclude that voucherless, sequence-based nomenclature is not a threat to specimen and culture-based fungal taxonomy, but a complementary approach capable of substantially closing the gap between known and predicted fungal diversity, an approach that requires careful work and high skill levels.

Sequence-based nomenclature: a reply to Thines et al. and Zamora et al. and provisions for an amended proposal "from the floor" to allow DNA sequences as types of names

We reply to two recently published, multi-authored opinion papers by opponents of sequence-based nomenclature, namely Zamora et al. (IMA Fungus9: 167-175,2018) and Thines et al. (IMA Fungus9: 177-183, 2018). While we agree with some of the principal arguments brought forward by these authors, we address misconceptions and demonstrate that some of the presumed evidence presented in these papers has been wrongly interpreted. We disagree that allowing sequences as types would fundamentally alter the nature of types, since a similar nature of abstracted features as type is already allowed in the Code (Art. 40.5), namely an illustration. We also disagree that there is a high risk of introducing artifactual taxa, as this risk can be quantified at well below 5 %, considering the various types of high-throughput sequencing errors. Contrary to apparently widespread misconceptions, sequence-based nomenclature cannot be based on similarity-derived OTUs and their consensus sequences, but must be derived from rigorous, multiple alignment-based phylogenetic methods and quantitative, single-marker species recognition algorithms, using original sequence reads; it is therefore identical in its approach to single-marker studies based on physical types, an approach allowed by the Code. We recognize the limitations of the ITS as a single fungal barcoding marker, but point out that these result in a conservative approach, with "false negatives" surpassing "false positives"; a desirable feature of sequence-based nomenclature. Sequence-based nomenclature does not aim at accurately resolving species, but at naming sequences that represent unknown fungal lineages so that these can serve as a means of communication, so ending the untenable situation of an exponentially growing number of unlabeled fungal sequences that fill online repositories. The risks are outweighed by the gains obtained by a reference library of named sequences spanning the full array of fungal diversity. Finally, we elaborate provisions in addition to our original proposal to amend the Code that would take care of the issues brought forward by opponents to this approach. In particular, taking up the idea of the Candidatus status of invalid, provisional names in prokaryote nomenclature, we propose a compromise that would allow valid publication of voucherless, sequence-based names in a consistent manner, but with the obligate designation as "nom. seq." (nomen sequentiae). Such names would not have priority over specimen- or culture-based names unless either epitypified with a physical type or adopted for protection on the recommendation of a committee of the International Commission on the Taxonomy of Fungi following evaluation based on strict quality control of the underlying studies based on established rules or recommendations.

Dual specificity phosphatase 5 and 6 are oppositely regulated in human skeletal muscle by acute exercise

Physical activity promotes specific adaptations in most tissues including skeletal muscle. Acute exercise activates numerous signaling cascades including pathways involving mitogen‐activated protein kinases (MAPKs) such as extracellular signal‐regulated kinase (ERK)1/2, which returns to pre‐exercise level after exercise. The expression of MAPK phosphatases (MKPs) in human skeletal muscle and their regulation by exercise have not been investigated before. In this study, we used mRNA sequencing to monitor regulation of MKPs in human skeletal muscle after acute cycling. In addition, primary human myotubes were used to gain more insights into the regulation of MKPs. The two ERK1/2‐specific MKPs, dual specificity phosphatase 5 (DUSP5) and DUSP6, were the most regulated MKPs in skeletal muscle after acute exercise. DUSP5 expression was ninefold higher immediately after exercise and returned to pre‐exercise level within 2 h, whereas DUSP6 expression was reduced by 43% just after exercise and remained below pre‐exercise level after 2 h recovery. Cultured myotubes express both MKPs, and incubation with dexamethasone (Dex) mimicked the in vivo expression pattern of DUSP5 and DUSP6 caused by exercise. Using a MAPK kinase inhibitor, we showed that stimulation of ERK1/2 activity by Dex was required for induction of DUSP5. However, maintaining basal ERK1/2 activity was required for basal DUSP6 expression suggesting that the effect of Dex on DUSP6 might involve an ERK1/2‐independent mechanism. We conclude that the altered expression of DUSP5 and DUSP6 in skeletal muscle after acute endurance exercise might affect ERK1/2 signaling of importance for adaptations in skeletal muscle during exercise.

Classifying nitrilases as aliphatic and aromatic using machine learning technique

ProCos (Protein Composition Server, script version), one of the machine learning techniques, was used to classify nitrilases as aliphatic and aromatic nitrilases. Some important feature vectors were used to train the algorithm, which included pseudo-amino acid composition (PAAC) and five-factor solution score (5FSS). This clearly differentiated into two groups of nitrilases, i.e., aliphatic and aromatic, achieving maximum sensitivity of 100.00%, specificity of 90.00%, accuracy of 95.00% and Mathew Correlation Coefficient (MCC) of about 0.90 for the pseudo-amino acid composition. On the other hand, five-factor solution score achieved a sensitivity of 96.00%, specificity of 84.00%, accuracy of 90.00% and Mathew Correlation Coefficient (MCC) of about 0.81. The total count of aliphatic amino acids, Ala (A), Gly (G), Leu (L), Ile (I), Val (V), Met (M) and Pro (P), was found to be higher, i.e., 42.7 in case of aliphatic nitrilases, whereas it was 40.1 in aromatic nitrilases. On the other hand, aromatic amino acids, Tyr (Y), Trp (W), His (H) and Phe (F) number, were found to be higher, i.e., 12.7 in aromatic nitrilases as compared to aliphatic nitrilases which was 10.7. This approach will help in predicting a nitrilase as aromatic or aliphatic nitrilase based on its amino acid sequence. Access to the scripts can be done logging onto GitHub using keyword 'Nitrilase' or 'https://github.com/rover2380/Nitrilase.git'.

Development of locus specific sub-clone separation by fluorescence in situ hybridization in suspension in chronic lymphocytic leukemia

Intra-tumor genetic heterogeneity is a hallmark of cancer. The ability to monitor and analyze these sub-clonal cell populations can be considered key to successful treatment, particularly in the modern era of targeted therapies. Although advances in sequencing technologies have significantly improved our ability to analyze the mutational landscape of tumors, this utility is reduced when considering small, but clinically significant sub-clones, that is, those representing <10% of the tumor burden. We have developed a high-throughput method that utilizes a 17-probe labeled bacterial artificial chromosome contig to quantify sub-clonal populations of cells based on deletion of a single locus. Chronic lymphocytic leukemia (CLL) cells harboring deletion of the short arm of chromosome 17 (del17p), an important prognostic marker for CLL were used to demonstrate the technique. Sub-clones of del17p cells were quantified and isolated from heterogeneous CLL populations using fluorescence in situ hybridization in suspension (FISH-IS) and the locus specific probe set. Using the combination of FISH-IS with the locus-specific probe set enables automated analysis of tens of thousands of cells, accurately quantifying and isolating cells carrying a del17p. Based on the fluorescence intensity of 17p probes, 17p (TP53) deleted cells were identified and sorted using flow cytometric techniques, and enrichment was demonstrated using single nucleotide polymorphism analysis. The ability to separate sub-clones of cells based on genetic heterogeneity, independent of the clone size, highlights the potential application of this method not only in the diagnostic and prognostic setting, but also as an unbiased approach to enable further detailed genetic analysis of the sub-clone with deep sequencing approaches. © 2017 International Society for Advancement of Cytometry.

Bioinformatics for NGS-based metagenomics and the application to biogas research

Metagenomics has proven to be one of the most important research fields for microbial ecology during the last decade. Starting from 16S rRNA marker gene analysis for the characterization of community compositions to whole metagenome shotgun sequencing which additionally allows for functional analysis, metagenomics has been applied in a wide spectrum of research areas. The cost reduction paired with the increase in the amount of data due to the advent of next-generation sequencing led to a rapidly growing demand for bioinformatic software in metagenomics. By now, a large number of tools that can be used to analyze metagenomic datasets has been developed. The Bielefeld-Gießen center for microbial bioinformatics as part of the German Network for Bioinformatics Infrastructure bundles and imparts expert knowledge in the analysis of metagenomic datasets, especially in research on microbial communities involved in anaerobic digestion residing in biogas reactors. In this review, we give an overview of the field of metagenomics, introduce into important bioinformatic tools and possible workflows, accompanied by application examples of biogas surveys successfully conducted at the Center for Biotechnology of Bielefeld University.

An efficient strategy using k-mers to analyse 16S rRNA sequences

The use of k-mers has been a successful strategy for improving metagenomics studies, including taxonomic classifications, or de novo assemblies, and can be used to obtain sequences of interest from the available databases. The aim of this manuscript was to propose a simple but efficient strategy to generate k-mers and to use them to obtain and analyse in silico 16S rRNA sequence fragments. A total of 513,309 bacterial sequences contained in the SILVA database were considered for the study, and homemade PHP scripts were used to search for specific nucleotide chains, recover fragments of bacterial sequences, make calculations and organize information. Consensus sequences matching conserved regions were constructed by aligning most of the primers used in the literature. Sequences of k nucleotides (9- to 15-mers) were extracted from the generated primer contigs. Frequency analysis revealed that k-mer size was inversely proportional to the occurrence of k-mers in the different conserved regions, suggesting a stringency relationship; high numbers of duplicate reactions were observed with short k-mers, and a lower proportion of sequences were obtained with large ones, with the best results obtained using 12-mers. Using 12-mers with the proposed method to obtain and study sequences was found to be a reliable approach for the analysis of 16S rRNA sequences and this strategy may probably be extended to other biomarkers. Furthermore, additional applications such as evaluating the degree of conservation and designing primers and other calculations are proposed as examples.

Taxonomy and systematics of plant probiotic bacteria in the genomic era

Recent decades have predicted significant changes within our concept of plant endophytes, from only a small number specific microorganisms being able to colonize plant tissues, to whole communities that live and interact with their hosts and each other. Many of these microorganisms are responsible for health status of the plant, and have become known in recent years as plant probiotics. Contrary to human probiotics, they belong to many different phyla and have usually had each genus analysed independently, which has resulted in lack of a complete taxonomic analysis as a group. This review scrutinizes the plant probiotic concept, and the taxonomic status of plant probiotic bacteria, based on both traditional and more recent approaches. Phylogenomic studies and genes with implications in plant-beneficial effects are discussed. This report covers some representative probiotic bacteria of the phylum Proteobacteria, Actinobacteria, Firmicutes and Bacteroidetes, but also includes minor representatives and less studied groups within these phyla which have been identified as plant probiotics.

Assessment of Common and Emerging Bioinformatics Pipelines for Targeted Metagenomics

Targeted metagenomics, also known as metagenetics, is a high-throughput sequencing application focusing on a nucleotide target in a microbiome to describe its taxonomic content. A wide range of bioinformatics pipelines are available to analyze sequencing outputs, and the choice of an appropriate tool is crucial and not trivial. No standard evaluation method exists for estimating the accuracy of a pipeline for targeted metagenomics analyses. This article proposes an evaluation protocol containing real and simulated targeted metagenomics datasets, and adequate metrics allowing us to study the impact of different variables on the biological interpretation of results. This protocol was used to compare six different bioinformatics pipelines in the basic user context: Three common ones (mothur, QIIME and BMP) based on a clustering-first approach and three emerging ones (Kraken, CLARK and One Codex) using an assignment-first approach. This study surprisingly reveals that the effect of sequencing errors has a bigger impact on the results that choosing different amplified regions. Moreover, increasing sequencing throughput increases richness overestimation, even more so for microbiota of high complexity. Finally, the choice of the reference database has a bigger impact on richness estimation for clustering-first pipelines, and on correct taxa identification for assignment-first pipelines. Using emerging assignment-first pipelines is a valid approach for targeted metagenomics analyses, with a quality of results comparable to popular clustering-first pipelines, even with an error-prone sequencing technology like Ion Torrent. However, those pipelines are highly sensitive to the quality of databases and their annotations, which makes clustering-first pipelines still the only reliable approach for studying microbiomes that are not well described.

Metavisitor, a Suite of Galaxy Tools for Simple and Rapid Detection and Discovery of Viruses in Deep Sequence Data

Metavisitor is a software package that allows biologists and clinicians without specialized bioinformatics expertise to detect and assemble viral genomes from deep sequence datasets. The package is composed of a set of modular bioinformatic tools and workflows that are implemented in the Galaxy framework. Using the graphical Galaxy workflow editor, users with minimal computational skills can use existing Metavisitor workflows or adapt them to suit specific needs by adding or modifying analysis modules. Metavisitor works with DNA, RNA or small RNA sequencing data over a range of read lengths and can use a combination of de novo and guided approaches to assemble genomes from sequencing reads. We show that the software has the potential for quick diagnosis as well as discovery of viruses from a vast array of organisms. Importantly, we provide here executable Metavisitor use cases, which increase the accessibility and transparency of the software, ultimately enabling biologists or clinicians to focus on biological or medical questions.

Bioinformatic Analyses of Unique (Orphan) Core Genes of the Genus Acidithiobacillus: Functional Inferences and Use As Molecular Probes for Genomic and Metagenomic/Transcriptomic Interrogation

Using phylogenomic and gene compositional analyses, five highly conserved gene families have been detected in the core genome of the phylogenetically coherent genus Acidithiobacillus of the class Acidithiobacillia. These core gene families are absent in the closest extant genus Thermithiobacillus tepidarius that subtends the Acidithiobacillus genus and roots the deepest in this class. The predicted proteins encoded by these core gene families are not detected by a BLAST search in the NCBI non-redundant database of more than 90 million proteins using a relaxed cut-off of 1.0e⁻⁵. None of the five families has a clear functional prediction. However, bioinformatic scrutiny, using pI prediction, motif/domain searches, cellular location predictions, genomic context analyses, and chromosome topology studies together with previously published transcriptomic and proteomic data, suggests that some may have functions associated with membrane remodeling during cell division perhaps in response to pH stress. Despite the high level of amino acid sequence conservation within each family, there is sufficient nucleotide variation of the respective genes to permit the use of the DNA sequences to distinguish different species of Acidithiobacillus, making them useful additions to the armamentarium of tools for phylogenetic analysis. Since the protein families are unique to the Acidithiobacillus genus, they can also be leveraged as probes to detect the genus in environmental metagenomes and metatranscriptomes, including industrial biomining operations, and acid mine drainage (AMD).

Environmental Viral Metagenomics Analyses in Aquaculture: Applications in Epidemiology and Disease Control

Studies on the epidemiology of viral diseases in aquaculture have for a long time depended on isolation of viruses from infected aquatic organisms. The role of aquatic environments in the epidemiology of viral diseases in aquaculture has not been extensively expounded mainly because of the lack of appropriate tools for environmental studies on aquatic viruses. However, the upcoming of metagenomics analyses opens great avenues in which environmental samples can be used to study the epidemiology of viral diseases outside their host species. Hence, in this review I have shown that epidemiological factors that influence the composition of viruses in different aquatic environments include ecological factors, anthropogenic activities and stocking densities of cultured organisms based on environmental metagenomics studies carried out this far. Ballast water transportation and global trade of aquatic organisms are the most common virus dispersal process identified this far. In terms of disease control for outdoor aquaculture systems, baseline data on viruses found in different environments intended for aquaculture use can be obtained to enable the design of effective disease control strategies. And as such, high-risk areas having a high specter of pathogenic viruses can be identified as an early warning system. As for the control of viral diseases for indoor recirculation aquaculture systems (RAS), the most effective disinfection methods able to eliminate pathogenic viruses from water used in RAS can be identified. Overall, the synopsis I have put forth in this review shows that environmental samples can be used to study the epidemiology of viral diseases in aquaculture using viral metagenomics analysis as an overture for the design of rational disease control strategies.

Reclassification of the taxonomic status of SEMIA3007 isolated in Mexico B-11A Mex as Rhizobium leguminosarum bv. viceae by bioinformatic tools

BACKGROUND

Evidence based on genomic sequences is extremely important to confirm the phylogenetic relationships within the Rhizobium group. SEMIA3007 was analyzed within the Mesorhizobium groups to define the underlying causes of taxonomic identification. We previously used biochemical tests and phenotypic taxonomic methods to identify bacteria, which can lead to erroneous classification. An improved understanding of bacterial strains such as the Mesorhizobium genus would increase our knowledge of classification and evolution of these species.

RESULTS

In this study, we sequenced the complete genome of SEMIA3007 and compared it with five other Mesorhizobium and two Rhizobium genomes. The genomes of isolated SEMIA3007 showed several orthologs with M. huakuii, M. erdmanii and M. loti. We identified SEMIA3007 as a Mesorhizobium by comparing the 16S rRNA gene and the complete genome.

CONCLUSION

Our ortholog, 16S rRNA gene and average nucleotide identity values (ANI) analysis all demonstrate SEMIA3007 is not Rhizobium leguminosarum bv. viceae. The results of the phylogenetic analysis clearly show SEMIA3007 is part of the Mesorhizobium group and suggest a reclassification is warranted.

Metagenomics, Metatranscriptomics, and Metabolomics Approaches for Microbiome Analysis

Microbiomes are ubiquitous and are found in the ocean, the soil, and in/on other living organisms. Changes in the microbiome can impact the health of the environmental niche in which they reside. In order to learn more about these communities, different approaches based on data from multiple omics have been pursued. Metagenomics produces a taxonomical profile of the sample, metatranscriptomics helps us to obtain a functional profile, and metabolomics completes the picture by determining which byproducts are being released into the environment. Although each approach provides valuable information separately, we show that, when combined, they paint a more comprehensive picture. We conclude with a review of network-based approaches as applied to integrative studies, which we believe holds the key to in-depth understanding of microbiomes.

Intestinal microbiota sustains inflammation and autoimmunity induced by hypomorphic RAG defects

Rigoni et al. report that hypomorphic Rag2^R229Q mutation is associated with altered microbiota composition and defects in the gut–blood barrier and suggest that intestinal microbes may play a critical role in the distinctive immune dysregulation of Omenn syndrome.

Omenn syndrome (OS) is caused by hypomorphic Rag mutations and characterized by a profound immunodeficiency associated with autoimmune-like manifestations. Both in humans and mice, OS is mediated by oligoclonal activated T and B cells. The role of microbial signals in disease pathogenesis is debated. Here, we show that Rag2^R229Q knock-in mice developed an inflammatory bowel disease affecting both the small bowel and colon. Lymphocytes were sufficient for disease induction, as intestinal CD4 T cells with a Th1/Th17 phenotype reproduced the pathological picture when transplanted into immunocompromised hosts. Moreover, oral tolerance was impaired in Rag2^R229Q mice, and transfer of wild-type (WT) regulatory T cells ameliorated bowel inflammation. Mucosal immunoglobulin A (IgA) deficiency in the gut resulted in enhanced absorption of microbial products and altered composition of commensal communities. The Rag2^R229Q microbiota further contributed to the immunopathology because its transplant into WT recipients promoted Th1/Th17 immune response. Consistently, long-term dosing of broad-spectrum antibiotics (ABXs) in Rag2^R229Q mice ameliorated intestinal and systemic autoimmunity by diminishing the frequency of mucosal and circulating gut-tropic CCR9⁺ Th1 and Th17 T cells. Remarkably, serum hyper-IgE, a hallmark of the disease, was also normalized by ABX treatment. These results indicate that intestinal microbes may play a critical role in the distinctive immune dysregulation of OS.

Unraveling the Functions of the Macroalgal Microbiome

Macroalgae are a diverse group of photosynthetic eukaryotic lower organisms and offer indispensable ecosystem services toward sustainable productivity of rocky coastal areas. The earlier studies have mainly focused on elucidation of the roles of the epiphytic bacterial communities in the ecophysiology of the host macroalga. However, mutualistic interactions have become topic of current interest. It is evident from recent studies that a fraction of epiphytic bacterial communities can be categorized as “core microbial species”, suggesting an obligate association. Epiphytic bacterial communities have also been reported to protect macroalgal surfaces from biofouling microorganisms through production of biologically active metabolites. Because of their intrinsic roles in the host life cycle, the host in turn may provide necessary organic nutrients in order to woo pelagic microbial communities to settle on the host surfaces. However, the precise composition of microbiomes and their functional partnership with hosts are hardly understood. In contrast, the microbial studies associated with human skin and gut and plants have significantly advanced our knowledge on microbiome and their functional interactions with the host. This has led to manipulation of the microbial flora of the human gut and of agricultural plants for improving health and performance. Therefore, it is highly imperative to investigate the functional microbiome that is closely involved in the life cycles of the host macroalgae using high-throughput techniques (metagenomics and metatranscriptomics). The findings from such investigations would help in promoting health and productivity in macroalgal species through regulation of functionally active microbiome.

The bovine milk microbiota: insights and perspectives from -omics studies

Recent findings and future perspectives of -omics studies on the bovine milk microbiota, focusing on its impact on animal health.

Novel Approaches to Apoptosis-Inducing Therapies

Induction of apoptotic programmed cell death is one of the underlying principles of most current cancer therapies. In this review, we discuss the limitations and drawbacks of this approach and identify three distinct, but overlapping strategies to avoid these difficulties and further enhance the efficacy of apoptosis-inducing therapies. We postulate that the application of multi-targeted small molecule inhibitor cocktails will reduce the risk of the cancer cell populations developing resistance towards therapy. Following from these considerations regarding population genetics and ecology, we advocate the reconsideration of therapeutic end points to maximise the benefits, in terms of quantity and quality of life, for the patients. Finally, combining both previous points, we also suggest an altered focus on the cellular and molecular targets of therapy, i.e. targeting the (cancer cells') interaction with the tumour microenvironment.

Metagenomic Classification Using an Abstraction Augmented Markov Model

The abstraction augmented Markov model (AAMM) is an extension of a Markov model that can be used for the analysis of genetic sequences. It is developed using the frequencies of all possible consecutive words with same length (p-mers). This article will review the theory behind AAMM and apply the theory behind AAMM in metagenomic classification.