The metagenomics RAST server - a public resource for the automatic phylogenetic and functional analysis of metagenomes

Luffa cylindrica (Sponge Gourd) Fibers in Treatment of Greywater: an Aerobic Fixed-Film Reactor Approach

The need for potable water consumption in urban and suburban regions can be decreased by greywater treatment and its reuse. Utilizing natural fibers may provide sustainable solutions in addressing challenges related to water resource management. In this study, a fixed-film reactor was designed with Luffa cylindrica (an annually occurring fruit) as a bio-carrier. The lab-scale reactors were configured with and without Luffa cylindrica and were run for 90 days in fed-batch mode. Scanning electron microscopy (SEM) was performed to validate biofilm production over time. Monitoring COD, nitrogen, and total phosphate removal allowed for analysis of treatment effectiveness. Results demonstrated the treatment efficiency for the experimental reactor was 70.96%, 97.02%, 92.57%, and 81.20% for COD, nitrogen, phosphate, and anionic surfactant (AS), respectively. 16 s rRNA gene sequencing of bio-carrier and control greywater samples was carried out. Many bacteria known to break down anionic surfactants were observed, and microbial succession was witnessed in the control reactor vs. the experimental reactor samples. The three most prevalent genera in the experimental samples were Chlorobium, Chlorobaculum, and Terrimonas. However, it is crucial to underscore that additional research is essential to solidify our understanding in this domain, with this study laying the fundamental groundwork.

Bioinformatic Approaches for Comparative Analysis of Viruses

The field of viral genomic studies has experienced an unprecedented increase in data volume. New strains of known viruses are constantly being added to the GenBank database and so are completely new species with little or no resemblance to our databases of sequences. In addition to this, metagenomic techniques have the potential to further increase the number and rate of sequenced genomes. Besides, it is important to consider that viruses have a set of unique features that often break down molecular biology dogmas, e.g., the flux of information from RNA to DNA in retroviruses and the use of RNA molecules as genomes. As a result, extracting meaningful information from viral genomes remains a challenge and standard methods for comparing the unknown and our databases of characterized sequences may need adaptations. Thus, several bioinformatic approaches and tools have been created to address the challenge of analyzing viral data. This chapter offers descriptions and protocols of some of the most important bioinformatic techniques for comparative analysis of viruses. The authors also provide comments and discussion on how viruses' unique features can affect standard analyses and how to overcome some of the major sources of problems. Protocols and topics emphasize online tools (which are more accessible to users) and give the real experience of what most bioinformaticians do in day-by-day work with command-line pipelines. The topics discussed include (1) clustering related genomes, (2) whole genome multiple sequence alignments for small RNA viruses, (3) protein alignment for marker genes and species affiliation, (4) variant calling and annotation, and (5) virome analyses and pathogen identification.

The interactive effects of ocean acidification and warming on bioeroding sponge Spheciospongia vesparium microbiome indicated by metatranscriptomics

Global climate change will cause coral reefs decline and is expected to increase the reef erosion potential of bioeroding sponges. Microbial symbionts are essential for the overall fitness and survival of sponge holobionts in changing ocean environments. However, we rarely know about the impacts of ocean warming and acidification on bioeroding sponge microbiome. Here, the structural and functional changes of the bioeroding sponge Spheciospongia vesparium microbiome, as well as its recovery potential, were investigated at the RNA level in a laboratory system simulating 32 °C and pH 7.7. Based on metatranscriptome analysis, acidification showed no significant impact, while warming or simultaneous warming and acidification disrupted the sponge microbiome. Warming caused microbial dysbiosis and recruited potentially opportunistic and pathogenic members of Nesiotobacter, Oceanospirillaceae, Deltaproteobacteria, Epsilonproteobacteria, Bacteroidetes and Firmicutes. Moreover, warming disrupted nutrient exchange and molecular interactions in the sponge holobiont, accompanied by stimulation of virulence activity and anaerobic metabolism including denitrification and dissimilatory reduction of nitrate and sulfate to promote sponge necrosis. Particularly, the interaction between acidification and warming alleviated the negative effects of warming and enhanced the Rhodobacteraceae-driven ethylmalonyl-CoA pathway and sulfur-oxidizing multienzyme system. The microbiome could not recover during the experiment period after warming or combined stress was removed. This study suggests that warming or combined warming and acidification will irreversibly destabilize the S. vesparium microbial community structure and function, and provides insight into the molecular mechanisms of the interactive effects of acidification and warming on the sponge microbiome.

Sketched reference databases for genome-based taxonomy and comparative genomics

Abstract The analysis of curated genomic, metagenomic and proteomic data is of paramount importance in the fields of biology, medicine, education, and bioinformatics. Although this type of data is usually hosted in raw format on free international repositories, the full access requires lots of computing power and large storage disk space for the domestic user. The purpose of the study is to offer a comprehensive set of microbial genomic and proteomic reference databases in an accessible and easy-to-use form to the scientific community and demonstrate its advantages and usefulness. Also, we present a case study on the applicability of the sketched data, for the determination of overall genomic coherence between two members of the Brucellacea family, which suggests they belong to the same genomospecies that remain as discrete ecotypes. A representative set of genomes, proteomes (from type material), and metagenomes were directly collected from the NCBI Assembly database and Genome Taxonomy Database (GTDB), associated with the major groups of Bacteria, Archaea, Virus, and Fungi. Sketched databases were subsequently created and stored on handy reduced representations by using the MinHash algorithm implemented in Mash software. The obtained dataset contains more than 133 GB of space disk reduced to 883.25 MB and represents 125,110 genomics/proteomic records from eight informative contexts, which have been prefiltered to make them accessible, usable, and user-friendly with limited computational resources. Potential uses of these sketched databases are discussed, including but not limited to microbial species delimitation, estimation of genomic distances and genomic novelties, paired comparisons between proteomes, genomes, and metagenomes; phylogenetic neighbor’s exploration and selection, among others.

Bacteria degrading both n-alkanes and aromatic hydrocarbons are prevalent in soils

This study was undertaken to determine the distribution of soil bacteria capable of utilizing both n-alkanes and aromatic hydrocarbons. These microorganisms have not been comprehensively investigated so far. Ten contaminated (4046-43,861 mg of total petroleum hydrocarbons (TPH) kg-1 of dry weight of soil) and five unpolluted (320-2754 mg TPH kg-1 of dry weight of soil) soil samples from temperate, arid, and Alpine soils were subjected to isolation of degraders with extended preferences and shotgun metagenomic sequencing (selected samples). The applied approach allowed to reveal that (a) these bacteria can be isolated from pristine and polluted soils, and (b) the distribution of alkane monooxygenase (alkB) and aromatic ring hydroxylating dioxygenases (ARHDs) encoding genes is not associated with the contamination presence. Some alkB and ARHD genes shared the same taxonomic affiliation; they were most often linked with the Rhodococcus, Pseudomonas, and Mycolicibacterium genera. Moreover, these taxa together with the Paeniglutamicibacter genus constituted the most numerous groups among 132 culturable strains growing in the presence of both n-alkanes and aromatic hydrocarbons. All those results indicate (a) the prevalence of the hydrocarbon degraders with extended preferences and (b) the potential of uncontaminated soil as a source of hydrocarbon degraders applied for bioremediation purposes.

Chronic industrial perturbation and seasonal change induces shift in the bacterial community from gammaproteobacteria to betaproteobacteria having catabolic potential for aromatic compounds at Amlakhadi canal

Escalating proportions of industrially contaminated sites are one of the major catastrophes faced at the present time due to the industrial revolution. The difficulties associated with culturing the microbes, has been circumvent by the direct use of metagenomic analysis of various complex niches. In this study, a metagenomic approach using next generation sequencing technologies was applied to exemplify the taxonomic abundance and metabolic potential of the microbial community residing in Amlakhadi canal, Ankleshwar at two different seasons. All the metagenomes revealed a predominance of Proteobacteria phylum. However, difference was observed within class level where Gammaproteobacteria was relatively high in polluted metagenome in Summer while in Monsoon the abundance shifted to Betaproteobacteria. Similarly, significant statistical differences were obtained while comparing the genera amongst contaminated sites where Serratia, Achromobacter, Stenotrophomonas and Pseudomonas were abundant in summer season and the dominance changed to Thiobacillus, Thauera, Acidovorax, Nitrosomonas, Sulfuricurvum, Novosphingobium, Hyphomonas and Geobacter in monsoon. Further upon functional characterization, the microbiomes revealed the diverse survival mechanisms, in response to the prevailing ecological conditions (such as degradation of aromatic compounds, heavy metal resistance, oxidative stress responses and multidrug resistance efflux pumps, etc.). The results have important implications in understanding and predicting the impacts of human-induced activities on microbial communities inhabiting natural niche and their responses in coping with the fluctuating pollution load.

Stepping towards pollen DNA metabarcoding: A breakthrough in forensic sciences

This review is engaged in determining the capability of plant pollen as a significant source of evidence for the linkage between suspects and crime location in forensic sciences. Research and review articles were collected from Google Scholar, the Web of Science, and PubMed. Articles were searched using specific keywords such as "Forensic Palynology," "Pollen metabarcoding," "Plant forensics," and "Pollen" AND "criminal investigation." Boolean logic was also utilized to narrow the articles to be included in this review article. Through the literature and exploratory research, it has been observed in the current study that with advancements in technology, forensic palynology has found its application in creating an association between the crime scene and suspected individuals to have a link to it, as pollen DNA is a long-lasting investigative tool that can effectively help forensic investigations. Moreover, the literature shows that the DNA of pollen and spores has helped forensic scientists link suspects to crime scenes, and the introduction of pollen DNA metabarcoding tools has eased the efforts of palynologists to analyze pollen DNA. The introduction of DNA metabarcoding techniques to analyze pollen from plants has helped identify the geological locations of the plants and ultimately identify the culprit.

Deep learning and CRISPR-Cas13d ortholog discovery for optimized RNA targeting

Effective and precise mammalian transcriptome engineering technologies are needed to accelerate biological discovery and RNA therapeutics. Despite the promise of programmable CRISPR-Cas13 ribonucleases, their utility has been hampered by an incomplete understanding of guide RNA design rules and cellular toxicity resulting from off-target or collateral RNA cleavage. Here, we quantified the performance of over 127,000 RfxCas13d (CasRx) guide RNAs and systematically evaluated seven machine learning models to build a guide efficiency prediction algorithm orthogonally validated across multiple human cell types. Deep learning model interpretation revealed preferred sequence motifs and secondary features for highly efficient guides. We next identified and screened 46 novel Cas13d orthologs, finding that DjCas13d achieves low cellular toxicity and high specificity-even when targeting abundant transcripts in sensitive cell types, including stem cells and neurons. Our Cas13d guide efficiency model was successfully generalized to DjCas13d, illustrating the power of combining machine learning with ortholog discovery to advance RNA targeting in human cells.

Metagenomics reveals effects of fluctuating water conditions on functional pathways in plant litter microbial community

Climate change modifies environmental conditions, resulting in altered precipitation patterns, moisture availability and nutrient distribution for microbial communities. Changes in water availability are projected to affect a range of ecological processes, including the decomposition of plant litter and carbon cycling. However, a detailed understanding of microbial stress response to drought/flooding is missing. In this study, an intermittent lake is taken up as a model for changes in water availability and how they affect the functional pathways in microbial communities of the decomposing Phragmites australis litter. The results show that most enriched functions in both habitats belonged to the classes of Carbohydrates and Clustering-based subsystems (terms with unknown function) from SEED subsystems classification. We confirmed that changes in water availability resulted in altered functional makeup of microbial communities. Our results indicate that microbial communities under more frequent water stress (due to fluctuating conditions) could sustain an additional metabolic cost due to the production or uptake of compatible solutes to maintain cellular osmotic balance. Nevertheless, although prolonged submergence seemed to have a negative impact on several functional traits in the fungal community, the decomposition rate was not affected.

Sequence-based Functional Metagenomics Reveals Novel Natural Diversity of Functional CopA in Environmental Microbiomes

Exploring the natural diversity of functional genes/proteins from environmental DNA in high throughput remains challenging. In this study, we developed a sequence-based functional metagenomics procedure for mining the diversity of copper (Cu) resistance gene copA in global microbiomes, by combining the metagenomic assembly technology, local BLAST, evolutionary trace analysis (ETA), chemical synthesis, and conventional functional genomics. In total, 87 metagenomes were collected from a public database and subjected to copA detection, resulting in 93,899 hits. Manual curation of 1214 hits of high confidence led to the retrieval of 517 unique CopA candidates, which were further subjected to ETA. Eventually, 175 novel copA sequences of high quality were discovered. Phylogenetic analysis showed that almost all these putative CopA proteins were distantly related to known CopA proteins, with 55 sequences from totally unknown species. Ten novel and three known copA genes were chemically synthesized for further functional genomic tests using the Cu-sensitive Escherichia coli (ΔcopA). The growth test and Cu uptake determination showed that five novel clones had positive effects on host Cu resistance and uptake. One recombinant harboring copA-like 15 (copAL15) successfully restored Cu resistance of the host with a substantially enhanced Cu uptake. Two novel copA genes were fused with the gfp gene and expressed in E. coli for microscopic observation. Imaging results showed that they were successfully expressed and their proteins were localized to the membrane. The results here greatly expand the diversity of known CopA proteins, and the sequence-based procedure developed overcomes biases in length, screening methods, and abundance of conventional functional metagenomics.

Metagenomics and metatranscriptomics as potential driving forces for the exploration of diversity and functions of micro-eukaryotes in soil

Micro-eukaryotes are ubiquitous and play vital roles in diverse ecological systems, yet their diversity and functions are scarcely known. This may be due to the limitations of formerly used conventional culture-based methods. Metagenomics and metatranscriptomics are enabling to unravel the genomic, metabolic, and phylogenetic diversity of micro-eukaryotes inhabiting in different ecosystems in a more comprehensive manner. The in-depth study of structural and functional characteristics of micro-eukaryote community residing in soil is crucial for the complete understanding of this major ecosystem. This review provides a deep insight into the methodologies employed under these approaches to study soil micro-eukaryotic organisms. Furthermore, the review describes available computational tools, pipelines, and database sources and their manipulation for the analysis of sequence data of micro-eukaryotic origin. The challenges and limitations of these approaches are also discussed in detail. In addition, this review summarizes the key findings of metagenomic and metatranscriptomic studies on soil micro-eukaryotes. It also highlights the exploitation of these methods to study the structural as well as functional profiles of soil micro-eukaryotic community and to screen functional eukaryotic protein coding genes for biotechnological applications along with the future perspectives in the field.

Datasets of shotgun metagenomics evaluation of rumen microbiota of South African mutton merino sheep

The rumen microbial consortium plays a crucial role in the production performance and health of the ruminant animal. They are responsible for breaking down complex plant materials such as cellulose and hemicellulose to release usable energy by the host animal. Rumen microbial diversity manipulation through dietary strategies can be used to achieve several goals such as improved feed efficiency, reduced environmental impact or better utilization of low-quality forages. The dataset, deposited in the National Centre for Biotechnology Information SRA with project number PRJNA775821, comprises sequenced DNA extracted from the rumen content of 16 South African Merino sheep supplemented with different plant extracts. Illumina HiSeq™ 6000 technology was utilised to generate a total of approximately 46.7 Gb in raw nucleotide data. The data consists of 700,318,582 sequences, each with an average length of 184 base pairs. Taxonomic annotation conducted through the MG-RAST server showed the dominant phylum averages are Bacteroidetes (51 %) and Firmicutes (28 %), while Euryarchaeota, Actinobacteria, and Proteobacteria each account for approximately 3 % of the population. This dataset also enables us to identify and profile all expressed genes related to metabolic and chemical processes. The dataset is a valuable tool, offering insights that can lead to enhanced sustainability, profitability and reduced environmental impact within the context of ruminant production process.

Application of high-throughput sequencing technologies and analytical tools for pathogen detection in urban water systems: Progress and future perspectives

The ubiquitous presence of pathogenic microorganisms, such as viruses, bacteria, fungi, and protozoa, in urban water systems poses a significant risk to public health. The emergence of infectious waterborne diseases mediated by urban water systems has become one of the leading global causes of mortality. However, the detection and monitoring of these pathogenic microorganisms have been limited by the complexity and diversity in the environmental samples. Conventional methods were restricted by long assay time, high benchmarks of identification, and narrow application sceneries. Novel technologies, such as high-throughput sequencing technologies, enable potentially full-spectrum detection of trace pathogenic microorganisms in complex environmental matrices. This review discusses the current state of high-throughput sequencing technologies for identifying pathogenic microorganisms in urban water systems with a concise summary. Furthermore, future perspectives in pathogen research emphasize the need for detection methods with high accuracy and sensitivity, the establishment of precise detection standards and procedures, and the significance of bioinformatics software and platforms. We have compiled a list of pathogens analysis software/platforms/databases that boast robust engines and high accuracy for preference. We highlight the significance of analyses by combining targeted and non-targeted sequencing technologies, short and long reads technologies, sequencing technologies, and bioinformatic tools in pursuing upgraded biosafety in urban water systems.

Structural and functional microbial diversity in deadwood respond to decomposition dynamics

We investigated the changes in microbial community diversities and functions in natural downed wood at different decay stages in a natural oak forest in the Italian Alps, through metagenomics analysis and in vitro analysis. Alfa diversity of bacterial communities was affected by the decay stage and log characteristics, while beta diversity was mainly driven by log diameter. Fungal and archaeal beta diversities were affected by the size of the sampled wood (log diameter), although, fungi were prominently driven by wood decay stage. The analysis of genes targeting cell wall degradation revealed higher abundances of cellulose and pectin-degrading enzymes in bacteria, while in fungi the enzymes targeting cellulose and hemicellulose were more abundant. The decay class affected the abundance of single enzymes, revealing a shift in complex hydrocarbons degradation pathways along the decay process. Moreover, we found that the genes related to Coenzyme M biosynthesis to be the most abundant especially at early stages of wood decomposition while the overall methanogenesis did not seem to be influenced by the decay stage. Intra- and inter-kingdom interactions between bacteria and fungi revealed complex pattern of community structure in response to decay stage possibly reflecting both direct and indirect interactions.

The Raphidiopsis (= Cylindrospermopsis) raciborskii pangenome updated: Two new metagenome-assembled genomes from the South American clade

Two Raphidiopsis (=Cylindrospermopsis) raciborskii metagenome-assembled genomes (MAGs) were recovered from two freshwater metagenomic datasets sampled in 2011 and 2012 in Pampulha Lake, a hypereutrophic, artificial, shallow reservoir, located in the city of Belo Horizonte (MG), Brazil. Since the late 1970s, the lake has undergone increasing eutrophication pressure, due to wastewater input, leading to the occurrence of frequent cyanobacterial blooms. The major difference observed between PAMP2011 and PAMP2012 MAGs was the lack of the saxitoxin gene cluster in PAMP2012, which also presented a smaller genome, while PAMP2011 presented the complete sxt cluster and all essential proteins and clusters. The pangenome analysis was performed with all Raphidiopsis/Cylindrospermopsis genomes available at NCBI to date, with the addition of PAMP2011 and PAMP2012 MAGs (All33 subset), but also without the South American strains (noSA subset), and only among the South American strains (SA10 and SA8 subsets). We observed a substantial increase in the core genome size for the 'noSA' subset, in comparison to 'All33' subset, and since the core genome reflects the closeness among the pangenome members, the results strongly suggest that the conservation level of the essential gene repertoire seems to be affected by the geographic origin of the strains being analyzed, supporting the existence of a distinct SA clade. The Raphidiopsis pangenome comprised a total of 7943 orthologous protein clusters, and the two new MAGs increased the pangenome size by 11%. The pangenome based phylogenetic relationships among the 33 analyzed genomes showed that the SA genomes clustered together with 99% bootstrap support, reinforcing the metabolic particularity of the Raphidiopsis South American clade, related to its saxitoxin producing unique ability, while also indicating a different evolutionary history due to its geographic isolation.

Dynamics of antimicrobial resistance and virulence of staphylococcal species isolated from foods traded in the Cape Coast metropolitan and Elmina municipality of Ghana

The impact of staphylococci on food poisoning and infections could be higher than previously reported. In this study, we characterised the occurrence and coexistence of antimicrobial resistance and virulence genes of staphylococci isolates in foods. Staphylococci were isolated from 236 samples of selected street-vended foods and identified. The pattern of antimicrobial resistance and virulence genes in the staphylococci were assessed using disc diffusion, PCR and analysis of next-generation sequencing data. The food samples (70.76 %) showed a high prevalence of staphylococci and differed among the food categories. Forty-five Staphylococcus species were identified and comprised coagulase-negative and positive species. Staphylococcus sciuri (now Mammaliicoccus sciuri), S. aureus, S. kloosii, S. xylosus, S. saprophyticus, S. haemolyticus and S. succinus were the most abundant species. The staphylococcal isolates exhibited resistance to tetracycline, levofloxacin, ciprofloxacin, norfloxacin, gentamicin and amikacin and susceptibility to nitrofurantoin. Antimicrobial susceptibilities were also reported for cefoperazone, ceftriaxone, cefotaxime, nalidixic acid and piperacillin-tazobactam. The antimicrobial resistance and virulence genes commonly detected consisted of tet, arl, macB, van, gyr, nor, optrA, bcrA, blaZ, taeA and S. aureus lmrS. The isolates frequently exhibited multiple resistance (30.42 %) of up to eight antimicrobial drug classes. The isolates predominantly harboured genes that express efflux pump proteins (50.53 %) for antibiotic resistance compared with inactivation (10.05 %), target alteration (26.72 %), protection (7.67 %) and replacement (3.17 %). The virulence determinants comprised genes of pyrogenic toxin superantigens (eta, etb, tst), adhesions (clf, fnbA, fnbB, cna, map, ebp, spA, vWbp, coa) and genes that express exoproteins (nuclease, metalloprotease, γ-hemolysin, hyaluronate lyase). There was a statistically significant difference in the prevalence of staphylococci isolates and their antimicrobial resistance and virulence profile as revealed by the phenotypic, PCR and next-generation sequencing techniques. The findings suggest a higher health risk for consumers. We recommend a critical need for awareness and antimicrobial susceptibility and anti-virulence strategies to ensure food safety and counteract the spread of this clinically relevant genus.

Life history strategies of soil bacterial communities across global terrestrial biomes

The life history strategies of soil microbes determine their metabolic potential and their response to environmental changes. Yet these strategies remain poorly understood. Here we use shotgun metagenomes from terrestrial biomes to characterize overarching covariations of the genomic traits that capture dominant life history strategies in bacterial communities. The emerging patterns show a triangle of life history strategies shaped by two trait dimensions, supporting previous theoretical and isolate-based studies. The first dimension ranges from streamlined genomes with simple metabolisms to larger genomes and expanded metabolic capacities. As metabolic capacities expand, bacterial communities increasingly differentiate along a second dimension that reflects a trade-off between increasing capacities for environmental responsiveness or for nutrient recycling. Random forest analyses show that soil pH, C:N ratio and precipitation patterns together drive the dominant life history strategy of soil bacterial communities and their biogeographic distribution. Our findings provide a trait-based framework to compare life history strategies of soil bacteria.

Challenges and opportunities in sharing microbiome data and analyses

Microbiome data, metadata and analytical workflows have become 'big' in terms of volume and complexity. Although the infrastructure and technologies to share data have been established, the interdisciplinary and multi-omic nature of the field can make resources difficult to identify and use. Following best practices for data deposition requires substantial effort, with sometimes little obvious reward. Gaps remain where microbiome-specific resources for data sharing or reproducibility do not yet exist. We outline available best practices, challenges to their adoption and opportunities in data sharing in microbiome research. We showcase examples of best practices and advocate for their enforcement and incentivization for data sharing. This includes recognition of data curation and sharing endeavours by individuals, institutions, journals and funders. Opportunities for progress include enabling microbiome-specific databases to incorporate future methods for data analysis, integration and reuse.

Functional conservation of microbial communities determines composition predictability in anaerobic digestion

A major challenge in managing and engineering microbial communities is determining whether and how microbial community responses to environmental alterations can be predicted and explained, especially in microorganism-driven systems. We addressed this challenge by monitoring microbial community responses to the periodic addition of the same feedstock throughout anaerobic digestion, a typical microorganism-driven system where microorganisms degrade and transform the feedstock. The immediate and delayed response consortia were assemblages of microorganisms whose abundances significantly increased on the first or third day after feedstock addition. The immediate response consortia were more predictable than the delayed response consortia and showed a reproducible and predictable order-level composition across multiple feedstock additions. These results stood in both present (16 S rRNA gene) and potentially active (16 S rRNA) microbial communities and in different feedstocks with different biodegradability and were validated by simulation modeling. Despite substantial species variability, the immediate response consortia aligned well with the reproducible CH4 production, which was attributed to the conservation of expressed functions by the response consortia throughout anaerobic digestion, based on metatranscriptomic data analyses. The high species variability might be attributed to intraspecific competition and contribute to biodiversity maintenance and functional redundancy. Our results demonstrate reproducible and predictable microbial community responses and their importance in stabilizing system functions.

Unveiling the early life core microbiome of the sea cucumber Apostichopus japonicus and the unexpected abundance of the growth-promoting Sulfitobacter

BACKGROUND

Microbiome in early life has long-term effects on the host's immunological and physiological development and its disturbance is known to trigger various diseases in host Deuterostome animals. The sea cucumber Apostichopus japonicus is one of the most valuable marine Deuterostome invertebrates in Asia and a model animal in regeneration studies. To understand factors that impact on host development and holobiont maintenance, host-microbiome association has been actively studied in the last decade. However, we currently lack knowledge of early life core microbiome during its ontogenesis and how it benefits the host's growth.

RESULTS

We analyzed the microbial community in 28 sea cucumber samples from a laboratory breeding system, designed to replicate aquaculture environments, across six developmental stages (fertilized eggs to the juvenile stage) over a three years-period to examine the microbiomes' dynamics and stability. Microbiome shifts occurred during sea cucumber larval ontogenesis in every case. Application of the most sophisticated core microbiome extraction methodology, a hybrid approach with abundance-occupancy core microbiome analyses (top 75% of total reads and > 70% occupation) and core index calculation, first revealed early life core microbiome consisted of Alteromonadaceae and Rhodobacteraceae, as well as a stage core microbiome consisting of pioneer core microbe Pseudoalteromonadaceae in A. japonicus, suggesting a stepwise establishment of microbiome related to ontogenesis and feeding behavior in A. japonicus. More interestingly, four ASVs affiliated to Alteromonadaceae and Rhodobacteraceae were extracted as early life core microbiome. One of the ASV (ASV0007) was affiliated to the Sulfitobactor strain BL28 (Rhodobacteraceae), isolated from blastula larvae in the 2019 raring batch. Unexpectedly, a bioassay revealed the BL28 strain retains a host growth-promoting ability. Further meta-pangenomics approach revealed the BL28 genome reads were abundant in the metagenomic sequence pool, in particular, in that of post-gut development in early life stages of A. japonicus.

CONCLUSION

Repeated rearing efforts of A. japonicus using laboratory aquaculture replicating aquaculture environments and hybrid core microbiome extraction approach first revealed particular ASVs affiliated to Alteromonadaceae and Rhodobacteraceae as the A. japonicus early life core microbiome. Further bioassay revealed the growth promoting ability to the host sea cucumber in one of the core microbes, the Sulfitobactor strain BL28 identified as ASV0007. Genome reads of the BL28 were abundant in post-gut development of A. japonicus, which makes us consider effective probiotic uses of those core microbiome for sea cucumber resource production and conservation. The study also emphasizes the importance of the core microbiome in influencing early life stages in marine invertebrates. Understanding these dynamics could offer pathways to improve growth, immunity, and disease resistance in marine invertebrates.

Exercise and microbiome: From big data to therapy

Exercise is a vital component in maintaining optimal health and serves as a prospective therapeutic intervention for various diseases. The human microbiome, comprised of trillions of microorganisms, plays a crucial role in overall health. Given the advancements in microbiome research, substantial databases have been created to decipher the functionality and mechanisms of the microbiome in health and disease contexts. This review presents an initial overview of microbiomics development and related databases, followed by an in-depth description of the multi-omics technologies for microbiome. It subsequently synthesizes the research pertaining to exercise-induced modifications of the microbiome and diseases that impact the microbiome. Finally, it highlights the potential therapeutic implications of an exercise-modulated microbiome in intestinal disease, obesity and diabetes, cardiovascular disease, and immune/inflammation-related diseases.

Primary choledocholithiasis occurrence and recurrence is synergetcally modulated by the bile microbiome and metabolome alternations

AIMS

Primary choledocholithiasis is a common digestive disease with high morbidity and relapse. However, the compositions and functions of the bile microbial ecosystem and the pathogenesis of microfloral regulation of host metabolism resulting in stone formation are poorly understood.

MAIN METHODS

Biliary samples collected from patients with acute cholangitis induced by benign biliary stricture (nonlithiasis group, n = 17) and primary choledocholithiasis (lithiasis group, n = 33) were subjected to multiomics analyses. Furthermore, clinicopathological features collected over a 24-month follow-up period were examined to evaluate the predictive value of candidate microbes.

KEY FINDINGS

Five alpha diversity indices of the bile microbiome were significantly decreased in the lithiasis group. Furthermore, we identified 49 differential bile flora between the two groups, and the relative abundances of 6 bacteria, Actinobacteria, Actinobacteriota, Staphylococcales, Micrococcales, Altererythrobacter and Carnobacteriaceae, were associated with primary choledocholithiasis relapse conditions. Multiomics analyses showed that specific changes in disease-related bacterial taxa were closely related to metabolite variation (low-molecular weight carboxylic acids, sterol liquid and acylcarnitine), which might reflect disease prognosis. According to microbiomic and metabolomic pathway analyses, we revealed that bacterial infections, microbiota-derived amino acid metabolites and secondary bile acid-related pathways were significantly enriched in the stone-formation group, suggesting a novel host-microbial metabolic mechanism of primary choledocholithiasis.

SIGNIFICANCE

Our study first indicates bile host-microbial dysbiosis modulates the abnormal accumulation of metabolites might further disrupt calcium homeostasis and generate insoluble saponification. Additionally, we determined the predictive value of Actinomycetes phylum reduction for recurrence in primary common bile duct stone patients.

A Pipeline for Constructing Reference Genomes for Large Cohort-Specific Metagenome Compression

Metagenomic data compression is very important as metagenomic projects are facing the challenges of larger data volumes per sample and more samples nowadays. Reference-based compression is a promising method to obtain a high compression ratio. However, existing microbial reference genome databases are not suitable to be directly used as references for compression due to their large size and redundancy, and different metagenomic cohorts often have various microbial compositions. We present a novel pipeline that generated simplified and tailored reference genomes for large metagenomic cohorts, enabling the reference-based compression of metagenomic data. We constructed customized reference genomes, ranging from 2.4 to 3.9 GB, for 29 real metagenomic datasets and evaluated their compression performance. Reference-based compression achieved an impressive compression ratio of over 20 for human whole-genome data and up to 33.8 for all samples, demonstrating a remarkable 4.5 times improvement than the standard Gzip compression. Our method provides new insights into reference-based metagenomic data compression and has a broad application potential for faster and cheaper data transfer, storage, and analysis.

Diversity of Microbiomes Across a 13,000-Year-Old Amazon Sediment

The microbiome is fundamental for understanding bacterial activities in sediments. However, only a limited number of studies have addressed the microbial diversity of Amazonian sediments. Here, we studied the microbiome of sediments from a 13,000-year BP core retrieved in a floodplain lake in Amazonia using metagenomics and biogeochemistry. Our aim was to evaluate the possible environmental influence over a river to a lake transition using a core sample. To this end, we sampled a core in the Airo Lake, a floodplain lake in the Negro River basin. The Negro River is the largest tributary of the Amazon River. The obtained core was divided into three strata: (i) surface, almost complete separation of the Airo Lake from the Negro River when the environment becomes more lentic with greater deposition of organic matter (black-colored sediment); (ii) transitional environment (reddish brown); and (iii) deep, environment with a tendency for greater past influence of the Negro River (brown color). The deepest sample possibly had the greatest influence of the Negro River as it represented the bottom of this river in the past, while the surface sample is the current Airo Lake bottom. In total, six metagenomes were obtained from the three different depth strata (total number of reads: 10.560.701; sequence length: 538 ± 24, mean ± standard deviation). The older (deeper) sediment strata contained a higher abundance of Burkholderia, Chitinophaga, Mucilaginibacter, and Geobacter, which represented ~ 25% of the metagenomic sequences. On the other hand, the more recent sediment strata had mainly Thermococcus, Termophilum, Sulfolobus, Archaeoglobus, and Methanosarcina (in total 11% of the metagenomic sequences). The sequence data were binned into metagenome-assembled genomes (MAGs). The majority of the obtained MAGs (n = 16) corresponded to unknown taxa, suggesting they may belong to new species. The older strata sediment microbiome was enriched with sulfur cycle genes, TCA cycle, YgfZ, and ATP-dependent proteolysis in bacteria. Meanwhile, serine-glyoxylate cycle, stress response genes, bacterial cell division, cell division-ribosomal stress protein cluster, and oxidative stress increased in the younger strata. Metal resistance and antimicrobial resistance genes were found across the entire core, including genes coding for fluoroquinolones, polymyxin, vancomycin, and multidrug resistance transporters. These findings depict the possible microbial diversity during the depositional past events and provided clues of the past microbial metabolism throughout time.

Snow Microorganisms Colonise Arctic Soils Following Snow Melt

Arctic soils are constantly subjected to microbial invasion from either airborne, marine, or animal sources, which may impact local microbial communities and ecosystem functioning. However, in winter, Arctic soils are isolated from outside sources other than snow, which is the sole source of microorganisms. Successful colonisation of soil by snow microorganisms depends on the ability to survive and compete of both, the invading and resident community. Using shallow shotgun metagenome sequencing and amplicon sequencing, this study monitored snow and soil microbial communities throughout snow melt to investigate the colonisation process of Arctic soils. Microbial colonisation likely occurred as all the characteristics of successful colonisation were observed. The colonising microorganisms originating from the snow were already adapted to the local environmental conditions and were subsequently subjected to many similar conditions in the Arctic soil. Furthermore, competition-related genes (e.g. motility and virulence) increased in snow samples as the snow melted. Overall, one hundred potentially successful colonisers were identified in the soil and, thus, demonstrated the deposition and growth of snow microorganisms in soils during melt.

Abundance and phylogenetic distribution of eight key enzymes of the phosphorus biogeochemical cycle in grassland soils

Grassland biomes provide valuable ecosystem services, including nutrient cycling. Organic phosphorus (Po) represents more than half of the total P in soils. Soil microorganisms release organic P through enzymatic processes, with alkaline phosphatases, acid phosphatases and phytases being the key P enzymes involved in the cycling of organic P. This study analysed 74 soil metagenomes from 17 different grassland biomes worldwide to evaluate the distribution and abundance of eight key P enzymes (PhoD, PhoX, PhoA, Nsap-A, Nsap-B, Nsap-C, BPP and CPhy) and their relationship with environmental factors. Our analyses showed that alkaline phosphatase phoD was the dataset's most abundant P-enzyme encoding genes, with a wide phylogenetic distribution. Followed by the acid phosphatases Nsap-A and Nsap-C showed similar abundance but a different distribution in their respective phylogenetic trees. Multivariate analyses revealed that pH, Tmax , SOC and soil moisture were associated with the abundance and diversity of all genes studied. PhoD and phoX genes strongly correlated with SOC and clay, and the phoX gene was more common in soils with low to medium SOC and neutral pH. In particular, P-enzyme genes tended to respond in a positively correlated manner among them, suggesting a complex relationship of abundance and diversity among them.

Long-term mitigation of drought changes the functional potential and life-strategies of the forest soil microbiome involved in organic matter decomposition

Climate change can alter the flow of nutrients and energy through terrestrial ecosystems. Using an inverse climate change field experiment in the central European Alps, we explored how long-term irrigation of a naturally drought-stressed pine forest altered the metabolic potential of the soil microbiome and its ability to decompose lignocellulolytic compounds as a critical ecosystem function. Drought mitigation by a decade of irrigation stimulated profound changes in the functional capacity encoded in the soil microbiome, revealing alterations in carbon and nitrogen metabolism as well as regulatory processes protecting microorganisms from starvation and desiccation. Despite the structural and functional shifts from oligotrophic to copiotrophic microbial lifestyles under irrigation and the observation that different microbial taxa were involved in the degradation of cellulose and lignin as determined by a time-series stable-isotope probing incubation experiment with 13C-labeled substrates, degradation rates of these compounds were not affected by different water availabilities. These findings provide new insights into the impact of precipitation changes on the soil microbiome and associated ecosystem functioning in a drought-prone pine forest and will help to improve our understanding of alterations in biogeochemical cycling under a changing climate.

Diversity and functional annotation of microorganisms in anaerobic chamber treating nitrate-rich wastewater

The vertical flow constructed wetlands (VFCW) for the treatment of domestic wastewater has become a conventional and cost effective treatment system with one of the major disadvantage of elevated nitrate concentrations. The present study makes an effort in providing a new design of anaerobic denitrification unit termed as anaerobic chamber (AC) which was introduced after two-stage VFCW to remove nitrates from the treated wastewater (WW). The AC provided all the essential conditions of effective denitrification such as anaerobic environment with enough carbon and nitrogen source. To understand the pollutant removal mechanism in AC, microbial diversity and functional annotation was studied by metagenomic analysis of sequences obtained from biofilm formed in AC. The efficiency of AC was measured with respect to physicochemical wastewater quality parameters. The removal efficiencies were 88, 65, 43 and 27% for total nitrogen, nitrate (NO3), ammoniacal-nitrogen (NH4) and ortho-phosphate respectively. The microbial flora was much more diverse and unique pertaining to anaerobic microbes in AC compared to WW with total of 954 and 1191 genuses respectively with minimum abundance of 10 hits. The metagenomes exhibited 188% more Archaea in the AC than WW where Crenarchaeota, Euryarchaeota, Korarchaeota, Nanoarchaeota and Thaumarchaeota were major phyla with 60 genuses. The nitrogen metabolism was reported in terms of assimilatory nitrate reductase. As the class, Proteobacteria, Actinobacteria were prominent in WW, whereas Proteobacteria, Chloroflexi in AC were abundant. From functional annotation of sequences, the microbial flora in AC has the potential of removal of pollutants present in the form of carbon, nitrogen, and phosphorus.

ARGem: a new metagenomics pipeline for antibiotic resistance genes: metadata, analysis, and visualization

Antibiotic resistance is of crucial interest to both human and animal medicine. It has been recognized that increased environmental monitoring of antibiotic resistance is needed. Metagenomic DNA sequencing is becoming an attractive method to profile antibiotic resistance genes (ARGs), including a special focus on pathogens. A number of computational pipelines are available and under development to support environmental ARG monitoring; the pipeline we present here is promising for general adoption for the purpose of harmonized global monitoring. Specifically, ARGem is a user-friendly pipeline that provides full-service analysis, from the initial DNA short reads to the final visualization of results. The capture of extensive metadata is also facilitated to support comparability across projects and broader monitoring goals. The ARGem pipeline offers efficient analysis of a modest number of samples along with affordable computational components, though the throughput could be increased through cloud resources, based on the user's configuration. The pipeline components were carefully assessed and selected to satisfy tradeoffs, balancing efficiency and flexibility. It was essential to provide a step to perform short read assembly in a reasonable time frame to ensure accurate annotation of identified ARGs. Comprehensive ARG and mobile genetic element databases are included in ARGem for annotation support. ARGem further includes an expandable set of analysis tools that include statistical and network analysis and supports various useful visualization techniques, including Cytoscape visualization of co-occurrence and correlation networks. The performance and flexibility of the ARGem pipeline is demonstrated with analysis of aquatic metagenomes. The pipeline is freely available at https://github.com/xlxlxlx/ARGem.

Uncultured prokaryotic genomes in the spotlight: An examination of publicly available data from metagenomics and single-cell genomics

Owing to the ineffectiveness of traditional culture techniques for the vast majority of microbial species, culture-independent analyses utilizing next-generation sequencing and bioinformatics have become essential for gaining insight into microbial ecology and function. This mini-review focuses on two essential methods for obtaining genetic information from uncultured prokaryotes, metagenomics and single-cell genomics. We analyzed the registration status of uncultured prokaryotic genome data from major public databases and assessed the advantages and limitations of both the methods. Metagenomics generates a significant quantity of sequence data and multiple prokaryotic genomes using straightforward experimental procedures. However, in ecosystems with high microbial diversity, such as soil, most genes are presented as brief, disconnected contigs, and lack association of highly conserved genes and mobile genetic elements with individual species genomes. Although technically more challenging, single-cell genomics offers valuable insights into complex ecosystems by providing strain-resolved genomes, addressing issues in metagenomics. Recent technological advancements, such as long-read sequencing, machine learning algorithms, and in silico protein structure prediction, in combination with vast genomic data, have the potential to overcome the current technical challenges and facilitate a deeper understanding of uncultured microbial ecosystems and microbial dark matter genes and proteins. In light of this, it is imperative that continued innovation in both methods and technologies take place to create high-quality reference genome databases that will support future microbial research and industrial applications.

Metagenomic Insights into the Microbiome and Resistance Genes of Traditional Fermented Foods in Arabia

This study uncovered microbial communities and evaluated the microbiological safety of traditional fermented foods consumed in the Arab region. Samples of dairy and non-dairy fermented foods-mish, jibneh, zabadi, and pickles-were collected from local markets in Saudi Arabia. Using the MiSeq system, samples were sequenced using 16S amplicons and shotgun metagenomics. Alpha and beta diversity indicated inter- and intra-variation in the studied fermented foods' bacterial communities. In the case of mish, the replicates were clustered. Twenty-one genera were found to be significantly different (FDR < 0.05) in abundance in pairwise comparison of fermented foods. Five high-quality, metagenome-assembled genomes (MAGs) of Lactococcus lactis, Lactobacillus helveticus, Pseudoalteromonas nigrifaciens, Streptococcus thermophiles, and Lactobacillus acetotolerans were retrieved from the shotgun sequencing representing the dominant taxa in the studied fermented foods. Additionally, 33 genes that cause antimicrobial resistance (ARGs) against ten different antibiotic classes were detected. Metabolic pathways were abundant in the studied metagenomes, such as amino acid metabolism, carbohydrate metabolism, cofactors, and vitamin biosynthesis. Metagenomic evaluation of Arabian fermented foods, including the identification of probiotics, pathogenic bacteria, and ARGs, illustrates the importance of microbiological analysis in evaluating their health effects.

Linking microbial slime community structure with abiotic factors and antifouling strategy in hydroelectric cooling systems

Microfouling can have significant economic impacts for hydroelectric power plants. However, knowledge concerning the composition and metabolism of microbial biofilm in cooling systems remains scarce. We examined the metagenome present in a cooling system, comprising a filter (F) and heat exchanger (HE), in the Nova Ponte hydroelectric power plant in Brazil, to identify bacteria and pathways that could be targeted to monitor and control biofilm formation. Our data revealed that the microfouling sample from heat exchanger 1 (HEM1), with porous consistency, presented enriched bacterial members not frequently described as biofilm formers in cooling systems, besides it has been shown to be an autoinducer repression pathway. Furthermore, the microfouling sample from heat exchanger 2 (HEM2), with gelatinous consistency, seemed to be an established biofilm, containing enriched bacterial groups such as Desulfotomaculum and Crenothrix and autoinducers, with biotechnological relevance in industrial biofilms. The results demonstrate that biofilm composition will vary depending on different abiotic conditions and the antifouling strategy used, including type of compound, concentration, and frequency of use. Therefore, all these variables must be evaluated when a power plant is affected by microbial slime in the cooling system. Our findings could help to define strategies for efficient and ecofriendly measures to contain microfouling in power plants.

Bacterial Colonization in the Airways and Intestines of Twin and Singleton Preterm Neonates: A Single-Center Study

Limited studies have investigated the microbial colonization of the airways and intestines in preterm neonates. We studied the composition of intestinal and airway bacterial colonies in several preterm twin pairs and singletons to explore the dominant bacteria, assess their variability, and predict their phenotypic and metabolic functions. In this descriptive study, we collected sputum and fetal stool specimens from 10 twin pairs (20 cases) and 20 singleton preterm neonates. These specimens were analyzed using 16S rRNA deep sequencing to study the alpha and beta diversities and community structures of airway and intestinal bacteria and predict their metabolic functions. Specimens from twins and singleton neonates had distinct aggregations of intestinal and airway bacteria but showed similarities and high microbial diversities during initial colonization. The top five phyla were Proteobacteria, Firmicutes, Actinobacteriota, Bacteroidota, and Cyanobacteria. The top ten genera were Streptococcus, Acinetobacter, Ralstonia, Staphylococcus, Comamonas, Enterococcus, Stenotrophomonas, Dechlorosoma, Sphingopyxis, and Rothia. Potentially pathogenic and highly stress-tolerant Gram-negative bacteria were predominant in the intestinal flora. A considerable proportion of colonies recovered from the airway and intestines of preterm neonates were functional bacteria. The richness of the intestinal and airway flora was not significantly different between twins and singletons, and the flora clustered together. Both intestinal and airway bacteria of twins and singletons were similar. The species involved in initial colonization were similar but different in proportions; therefore, changes in microbial structure and richness may not be attributed to these species.

Carnivorous Nepenthes Pitchers with Less Acidic Fluid House Nitrogen-Fixing Bacteria

Carnivorous pitcher plants are uniquely adapted to nitrogen limitation, using pitfall traps to acquire nutrients from insect prey. Pitcher plants in the genus Sarracenia may also use nitrogen fixed by bacteria inhabiting the aquatic microcosms of their pitchers. Here, we investigated whether species of a convergently evolved pitcher plant genus, Nepenthes, might also use bacterial nitrogen fixation as an alternative strategy for nitrogen capture. First, we constructed predicted metagenomes of pitcher organisms from three species of Singaporean Nepenthes using 16S rRNA sequence data and correlated predicted nifH abundances with metadata. Second, we used gene-specific primers to amplify and quantify the presence or absence of nifH directly from 102 environmental samples and identified potential diazotrophs with significant differential abundance in samples that also had positive nifH PCR tests. Third, we analyzed nifH in eight shotgun metagenomes from four additional Bornean Nepenthes species. Finally, we conducted an acetylene reduction assay using greenhouse-grown Nepenthes pitcher fluids to confirm nitrogen fixation is indeed possible within the pitcher habitat. Results show active acetylene reduction can occur in Nepenthes pitcher fluid. Variation in nifH from wild samples correlates with Nepenthes host species identity and pitcher fluid acidity. Nitrogen-fixing bacteria are associated with more neutral fluid pH, while endogenous Nepenthes digestive enzymes are most active at low fluid pH. We hypothesize Nepenthes species experience a trade-off in nitrogen acquisition; when fluids are acidic, nitrogen is primarily acquired via plant enzymatic degradation of insects, but when fluids are neutral, Nepenthes plants take up more nitrogen via bacterial nitrogen fixation. IMPORTANCE Plants use different strategies to obtain the nutrients that they need to grow. Some plants access their nitrogen directly from the soil, while others rely on microbes to access the nitrogen for them. Carnivorous pitcher plants generally trap and digest insect prey, using plant-derived enzymes to break down insect proteins and generate a large portion of the nitrogen that they subsequently absorb. In this study, we present results suggesting that bacteria living in the fluids formed by Nepenthes pitcher plants can fix nitrogen directly from the atmosphere, providing an alternative pathway for plants to access nitrogen. These nitrogen-fixing bacteria are only likely to be present when pitcher plant fluids are not strongly acidic. Interestingly, the plant's enzymes are known to be more active under strongly acidic conditions. We propose a potential trade-off where pitcher plants sometimes access nitrogen using their own enzymes to digest prey and at other times take advantage of bacterial nitrogen fixation.

Biological nitrogen fixation in the long-term nitrogen-fertilized and unfertilized paddy fields, with special reference to diazotrophic iron-reducing bacteria

Biological nitrogen fixation (BNF) is important to sustain nitrogen fertility of paddy soil and rice yield, while could be affected by nitrogen fertilization. Iron-reducing bacteria, Anaeromyxobacter and Geobacter, are newly found diazotrophic bacteria predominant in paddy soil. Experimental field of this study is a long-term (35 years) nitrogen fertilized (6.0 g N/m2/year) and unfertilized paddy field, where ca. 70% of rice yield was obtained yearly in nitrogen unfertilized plot (443 ± 37 g/m2) compared to fertilized plot (642 ± 64 g/m2). Effects of long-term nitrogen fertilization/unfertilization on soil properties related to BNF were investigated with special reference to diazotrophic iron-reducing bacteria. Soil chemical/biochemical properties, soil nitrogen-fixing activity, and community composition of diazotrophic bacteria were similar between nitrogen fertilized and unfertilized plot soils. In both plot soils, Anaeromyxobacter and Geobacter were the most predominant diazotrophs. Their nifD transcripts were detected at similar level, while those of other general diazotrophs were under detection limit. It was concluded that long-term use/unuse of nitrogen fertilizer in this field did not affect the predominance and nitrogen-fixing activity of diazotrophic iron-reducing bacteria, composition of other general diazotrophs, and the resulting soil nitrogen-fixing activity. BNF, primarily driven by diazotrophic iron-reducing bacteria, might significantly contribute to sustain soil nitrogen fertility and rice yield in both plot soils. Appropriate soil management to maintain BNF, including diazotrophic iron-reducing bacteria, will be important for sustainable soil nitrogen fertility and rice production.

Presence of an ultra-small microbiome in fermented cabbages

Background

Ultramicrobacteria (UMB), also known as ultra-small bacteria, are tiny bacteria with a size less than 0.1 µm³. They have a high surface-to-volume ratio and are found in various ecosystems, including the human body. UMB can be classified into two types: one formed through cell contraction and the other that maintains a small size. The ultra-small microbiome (USM), which may contain UMB, includes all bacteria less than 0.2 µm in size and is difficult to detect with current methods. However, it poses a potential threat to food hygiene, as it can pass through sterilization filters and exist in a viable but non-culturable (VBNC) state. The data on the USM of foods is limited. Some bacteria, including pathogenic species, are capable of forming UMB under harsh conditions, making it difficult to detect them through conventional culture techniques.

Methods

The study described above focused on exploring the diversity of USM in fermented cabbage samples from three different countries (South Korea, China, and Germany). The samples of fermented cabbage (kimchi, suancai, and sauerkraut) were purchased and stored in chilled conditions at approximately 4 °C until filtration. The filtration process involved two steps of tangential flow filtration (TFF) using TFF cartridges with different pore sizes (0.2 µm and 100 kDa) to separate normal size bacteria (NM) and USM. The USM and NM isolated via TFF were stored in a refrigerator at 4 °C until DNA extraction. The extracted DNA was then amplified using PCR and the full-length 16S rRNA gene was sequenced using single-molecule-real-time (SMRT) sequencing. The transmission electron microscope (TEM) was used to confirm the presence of microorganisms in the USM of fermented cabbage samples.

Results

To the best of our knowledge, this is the first study to identify the differences between USM and NM in fermented cabbages. Although the size of the USM (average 2,171,621 bp) was smaller than that of the NM (average 15,727,282 bp), diversity in USM (average H' = 1.32) was not lower than that in NM (average H' = 1.22). In addition, some members in USM probably underwent cell shrinkage due to unfavorable environments, while others maintained their size. Major pathogens were not detected in the USM in fermented cabbages. Nevertheless, several potentially suspicious strains (genera Cellulomonas and Ralstonia) were detected. Our method can be used to screen food materials for the presence of USM undetectable via conventional methods. USM and NM were efficiently separated using tangential flow filtration and analyzed via single-molecule real-time sequencing. The USM of fermented vegetables exhibited differences in size, diversity, and composition compared with the conventional microbiome. This study could provide new insights into the ultra-small ecosystem in fermented foods, including fermented cabbages.

Exploring resistomes and microbiomes in pilot-scale microalgae-bacteria wastewater treatment systems for use in low-resource settings

Antibiotic resistance genes (ARGs) released into the environment are an emerging human and environmental health concern, including ARGs spread in wastewater treatment effluents. In low-to-middle income countries (LMICs), an alternate wastewater treatment option instead of conventional systems are low-energy, high-rate algal ponds (HRAP) that use microalgae-bacteria aggregates (MABA) for waste degradation. Here we studied the robustness of ARG removal in MABA-based pilot-scale outdoor systems for 140 days of continuous operation. The HRAP system successfully removed 73 to 88 % chemical oxygen demand and up to 97.4 % ammonia, with aggregate size increasing over operating time. Fourteen ARG classes were identified in the HRAP influent, MABA, and effluent using metagenomics, with the HRAP process reducing total ARG abundances by up to 5-fold from influent to effluent. Parallel qPCR analyses showed the HRAP system significantly reduced exemplar ARGs (p < 0.05), with 1.2 to 4.9, 2.7 to 6.3, 0 to 1.5, and 1.2 to 4.8 log-removals for sul1, tetQ, blaKPC, and intl1 genes, respectively. Sequencing of influent, effluent and MABAs samples showed associated microbial communities differed significantly, with influent communities by Enterobacteriales (clinically relevant ARGs carrying bacteria), which were less evident in MABA and effluent. In this sense, such bacteria might be excluded from MABA due to their good settling properties and the presence of antimicrobial peptides. Microalgae-bacteria treatment systems steadily reduced ARGs from wastewater during operation time, using sunlight as the energetic driver, making them ideal for use in LMIC wastewater treatment applications.

Metagenomic approach to infer rumen microbiome derived traits of cattle

Ruminants enable the conversion of indigestible plant material into animal consumables, including dairy products, meat, and valuable fibers. Microbiome research is gaining popularity in livestock species because it aids in the knowledge of illnesses and efficiency processes in animals. In this study, we use WGS metagenomic data to thoroughly characterize the ruminal ecosystem of cows to infer positive and negative livestock traits determined by the microbiome. The rumen of cows from Argentina were described by combining different gene biomarkers, pathways composition and taxonomic information. Taxonomic characterization indicated that the two major phyla were Bacteroidetes and Firmicutes; in third place, Proteobacteria was highly represented followed by Actinobacteria; Prevotella, and Bacteroides were the most abundant genera. Functional profiling of carbohydrate-active enzymes indicated that members of the Glycoside Hydrolase (GH) class accounted for 52.2 to 55.6% of the total CAZymes detected, among them the most abundant were the oligosaccharide degrading enzymes. The diversity of GH families found suggested efficient hydrolysis of complex biomass. Genes of multidrug, macrolides, polymyxins, beta-lactams, rifamycins, tetracyclines, and bacitracin resistance were found below 0.12% of relative abundance. Furthermore, the clustering analysis of genera and genes that correlated to methane emissions or feed efficiency, suggested that the cows analysed could be regarded as low methane emitters and clustered with high feed efficiency reference animals. Finally, the combination of bioinformatic analyses used in this study can be applied to assess cattle traits difficult to measure and guide enhanced nutrition and breeding methods.

Meta-omics integration approach reveals the effect of soil native microbiome diversity in the performance of inoculant Azospirillum brasilense

Plant growth promoting bacteria (PGPB) have been used as integrative inputs to minimize the use of chemical fertilizers. However, a holistic comprehension about PGPB-plant-microbiome interactions is still incipient. Furthermore, the interaction among PGPB and the holobiont (host-microbiome association) represent a new frontier to plant breeding programs. We aimed to characterize maize bulk soil and rhizosphere microbiomes in irradiated soil (IS) and a native soil (NS) microbial community gradient (dilution-to-extinction) with Azospirillum brasilense Ab-V5, a PGPB commercial inoculant. Our hypothesis was that plant growth promotion efficiency is a result of PGPB niche occupation and persistence according to the holobiont conditions. The effects of Ab-V5 and NS microbial communities were evaluated in microcosms by a combined approach of microbiomics (species-specific qPCR, 16S rRNA metataxonomics and metagenomics) and plant phenomics (conventional and high-throughput methods). Our results revealed a weak maize growth promoting effect of Ab-V5 inoculation in undiluted NS, contrasting the positive effects of NS dilutions 10^-3, 10^-6, 10^-9 and IS with Ab-V5. Alpha diversity in NS + Ab-V5 soil samples was higher than in all other treatments in a time course of 25 days after sowing (DAS). At 15 DAS, alpha diversity indexes were different between NS and IS, but similar in all NS dilutions in rhizospheric samples. These differences were not persistent at 25 DAS, demonstrating a stabilization process in the rhizobiomes. In NS 10^-3 +Ab-V5 and NS 10^-6 Ab-V5, Ab-V5 persisted in the maize rhizosphere until 15 DAS in higher abundances compared to NS. In NS + Ab-V5, abundance of six taxa were positively correlated with response to (a)biotic stresses in plant-soil interface. Genes involved in bacterial metabolism of riboses and amino acids, and cresol degradation were abundant on NS 10^-3 + Ab-V5, indicating that these pathways can contribute to plant growth promotion and might be a result of Ab-V5 performance as a microbial recruiter of beneficial functions to the plant. Our results demonstrated the effects of holobiont on Ab-V5 performance. The meta-omics integration supported by plant phenomics opens new perspectives to better understanding of inoculants-holobiont interaction and for developing better strategies for optimization in the use of microbial products.

MetaPro: a scalable and reproducible data processing and analysis pipeline for metatranscriptomic investigation of microbial communities

BACKGROUND

Whole microbiome RNASeq (metatranscriptomics) has emerged as a powerful technology to functionally interrogate microbial communities. A key challenge is how best to process, analyze, and interpret these complex datasets. In a typical application, a single metatranscriptomic dataset may comprise from tens to hundreds of millions of sequence reads. These reads must first be processed and filtered for low quality and potential contaminants, before being annotated with taxonomic and functional labels and subsequently collated to generate global bacterial gene expression profiles.

RESULTS

Here, we present MetaPro, a flexible, massively scalable metatranscriptomic data analysis pipeline that is cross-platform compatible through its implementation within a Docker framework. MetaPro starts with raw sequence read input (single-end or paired-end reads) and processes them through a tiered series of filtering, assembly, and annotation steps. In addition to yielding a final list of bacterial genes and their relative expression, MetaPro delivers a taxonomic breakdown based on the consensus of complementary prediction algorithms, together with a focused breakdown of enzymes, readily visualized through the Cytoscape network visualization tool. We benchmark the performance of MetaPro against two current state-of-the-art pipelines and demonstrate improved performance and functionality.

CONCLUSIONS

MetaPro represents an effective integrated solution for the processing and analysis of metatranscriptomic datasets. Its modular architecture allows new algorithms to be deployed as they are developed, ensuring its longevity. To aid user uptake of the pipeline, MetaPro, together with an established tutorial that has been developed for educational purposes, is made freely available at https://github.com/ParkinsonLab/MetaPro . The software is freely available under the GNU general public license v3. Video Abstract.

Dietary berberine against intestinal oxidative stress, inflammation response, and microbiota disturbance caused by chronic copper exposure in freshwater grouper (Acrossocheilus fasciatus)

Berberine (BBR) is known for its strong antioxidant, anti-inflammatory, and capacity to preserve intestinal microbiota balance in fish. This study aimed to investigate the protective effects of berberine against copper-induced toxicity in the intestine of freshwater grouper Acrossocheilus fasciatus. The experiment involved four groups: a control group, a Cu group exposed to 0.02 mg/L Cu²⁺, and two BBR groups fed with 100 or 400 mg/kg of berberine diets and exposed to the same Cu²⁺ concentration. Three replicates of healthy fish (initial weight 1.56 ± 0.10 g) were subjected to their respective treatments for 30 days. Results showed that none of the treatments significantly affected the survival rate, final weight, weight gain, and feed intake (P > 0.05). However, supplementation with 100 and 400 mg/kg of BBR significantly lowered the antioxidant activities, and glutathione peroxidase (gpx) and superoxide dismutase (sod) expression levels, as well as reduced malondialdehyde (MDA) content caused by Cu²⁺ exposure (P < 0.05). Berberine inclusion significantly downregulated proinflammatory factors NLR family pyrin domain containing 3 (nlrp3), interleukin 1 beta (il1β), interleukin 6 cytokine family signal transducer (il6st) but upregulated transforming growth factor beta 1 (tgfβ1) and heat shock 70kDa protein (hsp70) expression. Moreover, berberine at both levels maintained the intestinal structural integrity and significantly improved gap junction gamma-1 (gjc1) mRNA level compared to the Cu group (P < 0.05). Based on 16S rDNA sequencing, the richness and diversity of intestinal microbiota in different groups were not significantly influenced. Berberine reduced the Firmicutes/Bacteroidota ratio and stifled the growth of some specific pathogenic bacteria such as Pseudomonas, Citrobacter, and Acinetobacter, while boosting the richness of potential probiotic bacteria, including Roseomonas and Reyranella compared with the Cu group. In conclusion, berberine showed significant protective effects against Cu²⁺-induced intestinal oxidative stress, inflammation response, and microbiota disturbance in freshwater grouper.

Comprehensive analysis of the microbiome and metabolome in pus from pyogenic liver abscess patients with and without diabetes mellitus

Introduction

Pyogenic liver abscess (PLA) patients combined with diabetes mellitus (DM) tend to have more severe clinical manifestations than without DM. The mechanism responsible for this phenomenon is not entirely clear. The current study therefore aimed to comprehensively analyze the microbiome composition and metabolome in pus from PLA patients with and without DM, to determine the potential reasons for these differences.

Methods

Clinical data from 290 PLA patients were collected retrospectively. We analyzed the pus microbiota using 16S rDNA sequencing in 62 PLA patients. In addition, the pus metabolomes of 38 pus samples were characterized by untargeted metabolomics analysis. Correlation analyses of microbiota, metabolites and laboratory findings were performed to identify significant associations.

Results

PLA patients with DM had more severe clinical manifestations than PLA patients without DM. There were 17 discriminating genera between the two groups at the genus level, among which Klebsiella was the most discriminating taxa. The ABC transporters was the most significant differential metabolic pathway predicted by PICRUSt2. Untargeted metabolomics analysis showed that concentrations of various metabolites were significantly different between the two groups and seven metabolites were enriched in the ABC transporters pathway. Phosphoric acid, taurine, and orthophosphate in the ABC transporters pathway were negatively correlated with the relative abundance of Klebsiella and the blood glucose level.

Discussion

The results showed that the relative abundance of Klebsiella in the pus cavity of PLA patients with DM was higher than those without DM, accompanied by changes of various metabolites and metabolic pathways, which may be associated with more severe clinical manifestations.

MiSurv: an Integrative Web Cloud Platform for User-Friendly Microbiome Data Analysis with Survival Responses

Investigators have studied the treatment effects on human health or disease, the treatment effects on human microbiome, and the roles of the microbiome on human health or disease. Especially, in a clinical trial, investigators commonly trace disease status over a lengthy period to survey the sequential disease progression for different treatment groups (e.g., treatment versus placebo, new treatment versus old treatment). Hence, disease responses are often available in the form of survival (i.e., time-to-event) responses stratified by treatment groups. While the recent web cloud platforms have enabled user-friendly microbiome data processing and analytics, there is currently no web cloud platform to analyze microbiome data with survival responses. Therefore, we introduce here an integrative web cloud platform, called MiSurv, for comprehensive microbiome data analysis with survival responses. IMPORTANCE MiSurv consists of a data processing module and its following four data analytic modules: (i) Module 1: Comparative survival analysis between treatment groups, (ii) Module 2: Comparative analysis in microbial composition between treatment groups, (iii) Module 3: Association testing between microbial composition and survival responses, (iv) Module 4: Prediction modeling using microbial taxa on survival responses. We demonstrate its use through an example trial on the effects of antibiotic use on the survival rate against type 1 diabetes (T1D) onset and gut microbiome composition, respectively, and the effects of the gut microbiome on the survival rate against T1D onset. MiSurv is freely available on our web server (http://misurv.micloud.kr) or can alternatively run on the user's local computer (https://github.com/wg99526/MiSurvGit).

The impacts of ocean acidification, warming and their interactive effects on coral prokaryotic symbionts

BACKGROUND

Reef-building corals, the foundation of tropical coral reefs, are vulnerable to climate change e.g. ocean acidification and elevated seawater temperature. Coral microbiome plays a key role in host acclimatization and maintenance of the coral holobiont's homeostasis under different environmental conditions, however, the response patterns of coral prokaryotic symbionts to ocean acidification and/or warming are rarely known at the metatranscriptional level, particularly the knowledge of interactive and persistent effects is limited. Using branching Acropora valida and massive Galaxea fascicularis as models in a lab system simulating extreme ocean acidification (pH 7.7) and/or warming (32 °C) in the future, we investigated the changes of in situ active prokaryotic symbionts community and gene expression of corals under/after (6/9 d) acidification (A), warming (H) and acidification-warming (AH) by metatranscriptome analysis with pH8.1, 26 °C as the control.

RESULTS

A, H and AH increased the relative abundance of in situ active pathogenic bacteria. Differentially expressed genes (DEGs) involved in virulence, stress resistance, and heat shock proteins were up-regulated. Many DEGs involved in photosynthesis, carbon dioxide fixation, amino acids, cofactors and vitamins, auxin synthesis were down-regulated. A broad array of new DEGs involved in carbohydrate metabolism and energy production emerged after the stress treatment. Different response patterns of prokaryotic symbionts of massive G. fascicularis and branching A. valida were suggested, as well as the interactive effects of combined AH and persistent effects.

CONCLUSIONS

The metatranscriptome-based study indicates that acidification and/or warming might change coral's in situ active prokaryotic microbial diversity and functional gene expression towards more pathogenic and destabilized coral-microbes symbioses, particularly combined acidification and warming show interactive effects. These findings will aid in comprehension of the coral holobiont's ability for acclimatization under future climate change.

Unraveling the functional genes present in rhizosphere microbiomes of Solanum lycopersicum

The microbiomes living in the rhizosphere soil of the tomato plant contribute immensely to the state of health of the tomato plant alongside improving sustainable agriculture. With the aid of shotgun metagenomics sequencing, we characterized the putative functional genes (plant-growth-promoting and disease-resistant genes) produced by the microbial communities dwelling in the rhizosphere soil of healthy and powdery mildew-diseased tomato plants. The results identified twenty-one (21) plant growth promotion (PGP) genes in the microbiomes inhabiting the healthy rhizosphere (HR) which are more predomiant as compared to diseased rhizosphere (DR) that has nine (9) genes and four (4) genes in bulk soil (BR). Likewise, we identified some disease-resistant genes which include nucleotide binding genes and antimicrobial genes. Our study revealed fifteen (15) genes in HR which made it greater in comparison to DR that has three (3) genes and three (3) genes in bulk soil. Further studies should be conducted by isolating these microorganisms and introduce them to field experiments for cultivation of tomatoes.

Shotgun metagenomics dataset of Striga hermonthica-infested maize (Zea mays L.) rhizospheric soil microbiome

This dataset includes shotgun metagenomics sequencing of the rhizosphere microbiome of maize infested with Striga hermonthica from Mbuzini, South Africa, and Eruwa, Nigeria. The sequences were used for microbial taxonomic classification and functional categories in the infested maize rhizosphere. High throughput sequencing of the complete microbial community's DNA was performed using the Illumina NovaSeq 6000 technology. The average base pair count of the sequences were 5,353,206 bp with G+C content of 67%. The raw sequence data used for analysis is available in NCBI under the BioProject accession numbers PRJNA888840 and PRJNA889583. The taxonomic analysis was performed using Metagenomic Rapid Annotations using Subsystems Technology (MG-RAST). Bacteria had the highest taxonomic representation (98.8%), followed by eukaryotes (0.56%), and archaea (0.45%). This metagenome dataset provide valuable information on microbial communities associated with Striga-infested maize rhizosphere and their functionality. It can also be used for further studies on application of microbial resources for sustainable crop production in this region.

Dataset of shotgun metagenomic evaluation of lettuce (Lactuta sativa L.) rhizosphere microbiome

Lettuce (Lactuca sativa L.) is an important vegetable grown and consumed across the world, including South Africa and its rhizosphere constitutes a dynamic community of root associated microbes. Dataset of the microbial community profile of the lettuce rhizospheric soils obtained from Talton, Gauteng Province of South Africa was subjected to metagenomic evaluation using the shotgun approach. The whole DNA isolated from the community was sequenced using NovaSeq 6000 system (Illumina). The raw data obtained consists of 129,063,513.33 sequences with an average length of 200 base pairs and 60.6% Guanine + Cytosine content. The metagenome data has been deposited to the National Centre for Biotechnology Information SRA under the bioproject number PRJNA763048. The downstream analysis alongside taxonomical annotation carried out using an online server MG-RAST, showed the community analysis as being made up of archaea (0.95%), eukaryotes (1.36%), viruses (0.04%), while 97.65% of the sequences were classified as bacteria. A sum of 25 bacteria, 20 eukaryotic and 4 archaea phyla were identified. The predominant genera were Acinetobacter (4.85%), Pseudomonas (3.41%), Streptomyces (2.79%), Candidatus solibacter (1.93%), Burkholderia (1.65%), Bradyrhizobium (1.51%) and Mycobacterium (1.31%). Annotation using Cluster of Orthologous Group (COG) showed 23.91% of the sequenced data were for metabolic function, 33.08% for chemical process and signaling while 6.42% were poorly characterized. Furthermore, the subsystem annotation method showed that sequences were majorly associated with carbohydrates (12.86%), clustering-based subsystems (12.68%), and genes coding for amino acids and derivatives (10.04%), all of which could serve in growth promotion and plant management.

Modularity and diversity of target selectors in Tn7 transposons

To spread, transposons must integrate into target sites without disruption of essential genes while avoiding host defense systems. Tn7-like transposons employ multiple mechanisms for target-site selection, including protein-guided targeting and, in CRISPR-associated transposons (CASTs), RNA-guided targeting. Combining phylogenomic and structural analyses, we conducted a broad survey of target selectors, revealing diverse mechanisms used by Tn7 to recognize target sites, including previously uncharacterized target-selector proteins found in newly discovered transposable elements (TEs). We experimentally characterized a CAST I-D system and a Tn6022-like transposon that uses TnsF, which contains an inactivated tyrosine recombinase domain, to target the comM gene. Additionally, we identified a non-Tn7 transposon, Tsy, encoding a homolog of TnsF with an active tyrosine recombinase domain, which we show also inserts into comM. Our findings show that Tn7 transposons employ modular architecture and co-opt target selectors from various sources to optimize target selection and drive transposon spread.

Biological and green remediation of heavy metal contaminated water and soils: A state-of-the-art review

Contamination of the natural ecosystem by heavy metals, organic pollutants, and hazardous waste severely impacts on health and survival of humans, animals, plants, and microorganisms. Diverse chemical and physical treatments are employed in many countries, however, the acceptance of these treatments are usually poor because of taking longer time, high cost, and ineffectiveness in contaminated areas with a very high level of metal contents. Bioremediation is an eco-friendly and efficient method of reclaiming contaminated soils and waters with heavy metals through biological mechanisms using potential microorganisms and plant species. Considering the high efficacy, low cost, and abundant availability of biological materials, particularly bacteria, algae, yeasts, and fungi, either in natural or genetically engineered (GE) form, bioremediation is receiving high attention for heavy metal removal. This report comprehensively reviews and critically discusses the biological and green remediation tactics, contemporary technological advances, and their principal applications either in-situ or ex-situ for the remediation of heavy metal contamination in soil and water. A modified PRISMA review protocol is adapted to critically assess the existing research gaps in heavy metals remediation using green and biological drivers. This study pioneers a schematic illustration of the underlying mechanisms of heavy metal bioremediation. Precisely, it pinpoints the research bottleneck during its real-world application as a low-cost and sustainable technology.

Chemical Links Between Redox Conditions and Estimated Community Proteomes from 16S rRNA and Reference Protein Sequences

Environmental influences on community structure are often assessed through multivariate analyses in order to relate microbial abundances to separately measured physicochemical variables. However, genes and proteins are themselves chemical entities; in combination with genome databases, differences in microbial abundances directly encode for chemical variability. We predicted that the carbon oxidation state of estimated community proteomes, obtained by combining taxonomic abundances from published 16S rRNA gene sequencing datasets with reference microbial proteomes from the NCBI Reference Sequence (RefSeq) database, would reflect environmental oxidation-reduction conditions. Analysis of multiple datasets confirms the geobiochemical predictions for environmental redox gradients in hydrothermal systems, stratified lakes and marine environments, and shale gas wells. The geobiochemical signal is largest for the steep redox gradients associated with hydrothermal systems and between injected water and produced fluids from shale gas wells, demonstrating that microbial community composition can be a chemical proxy for environmental redox gradients. Although estimates of oxidation state from 16S amplicon and metagenomic sequences are correlated, the 16S-based estimates show stronger associations with redox gradients in some environments.