http://www.microbiologyresearch.org/content/journal/mgen?TRACK=RSS Please follow the links to view the content. http://www.microbiologyresearch.org/content/journal/mgen/10.1099/mgen.0.001322?TRACK=RSS Because large brains are energetically expensive, they are associated with metabolic traits that facilitate energy availability across vertebrates. However, the biological underpinnings driving these traits are not known. Given its role in regulating host metabolism in disease studies, we hypothesized that the gut microbiome contributes to variation in normal cross-vertebrate species differences in metabolism, including those associated with the brain’s energetic requirements. By inoculating germ-free mice with the gut microbiota (GM) of three primate species – two with relatively larger brains and one with a smaller brain – we demonstrated that the GM of larger-brained primates shifts host metabolism towards energy use and production, while that of smaller-brained primates stimulates energy storage in adipose tissues. Our findings establish a causal role of the GM in normal cross-host species differences in metabolism associated with relative brain size and suggest that the GM may have been an important facilitator of metabolic changes during human evolution that supported encephalization. Elizabeth K. Mallott, Sahana Kuthyar, Won Lee, Derek Reiman, Hongmei Jiang, Sriram Chitta, E. Alexandria Waters, Brian T. Layden, Ronen Sumagin, Laura D. Manzanares, Guan-Yu Yang, Maria Luisa Savo Sardaro, Stanton Gray, Lawrence E. Williams, Yang Dai, James P. Curley, Chad R. Haney, Emma R. Liechty, Christopher W. Kuzawa and Katherine R. Amato 2024-12-02T12:47:05Z http://www.microbiologyresearch.org/content/journal/mgen/10.1099/mgen.0.000685?TRACK=RSS Command-line annotation software tools have continuously gained popularity compared to centralized online services due to the worldwide increase of sequenced bacterial genomes. However, results of existing command-line software pipelines heavily depend on taxon-specific databases or sufficiently well annotated reference genomes. Here, we introduce Bakta, a new command-line software tool for the robust, taxon-independent, thorough and, nonetheless, fast annotation of bacterial genomes. Bakta conducts a comprehensive annotation workflow including the detection of small proteins taking into account replicon metadata. The annotation of coding sequences is accelerated via an alignment-free sequence identification approach that in addition facilitates the precise assignment of public database cross-references. Annotation results are exported in GFF3 and International Nucleotide Sequence Database Collaboration (INSDC)-compliant flat files, as well as comprehensive JSON files, facilitating automated downstream analysis. We compared Bakta to other rapid contemporary command-line annotation software tools in both targeted and taxonomically broad benchmarks including isolates and metagenomic-assembled genomes. We demonstrated that Bakta outperforms other tools in terms of functional annotations, the assignment of functional categories and database cross-references, whilst providing comparable wall-clock runtimes. Bakta is implemented in Python 3 and runs on MacOS and Linux systems. It is freely available under a GPLv3 license at https://github.com/oschwengers/bakta. An accompanying web version is available at https://bakta.computational.bio. Oliver Schwengers, Lukas Jelonek, Marius Alfred Dieckmann, Sebastian Beyvers, Jochen Blom and Alexander Goesmann 2021-11-05T16:44:00Z http://www.microbiologyresearch.org/content/journal/mgen/10.1099/mgen.0.001308?TRACK=RSS Antimicrobial resistance (AMR) poses a significant threat to global public health, with the potential to cause millions of deaths annually by 2050. Effective surveillance of AMR pathogens is crucial for monitoring and predicting their behaviour in response to antibiotics. However, many public health professionals lack the necessary bioinformatics skills and resources to analyse pathogen genomes effectively. To address this challenge, we developed AMRColab, an open-access bioinformatics analysis suite hosted on Google Colaboratory. AMRColab enables users with limited or no bioinformatics training to detect and visualize AMR determinants in pathogen genomes using a ‘plug-and-play’ approach. The platform integrates established bioinformatics tools such as AMRFinderPlus and hAMRonization, allowing users to analyse, compare and visualize trends in AMR pathogens easily. A trial run using methicillin-resistant Staphylococcus aureus (MRSA) strains demonstrated AMRColab’s effectiveness in identifying AMR determinants and facilitating comparative analysis across strains. A workshop was conducted and feedback from participants indicated high confidence in using AMRColab and a willingness to incorporate it into their research. AMRColab’s user-friendly interface and modular design make it accessible to a diverse audience, including medical laboratory technologists, medical doctors and public health scientists, regardless of their bioinformatics expertise. Future improvements to AMRColab will include enhanced visualization tools, multilingual support and the establishment of an online community platform. AMRColab represents a significant step towards democratizing AMR surveillance and empowering public health professionals to combat AMR effectively. Su Datt Lam, Sabrina Di Gregorio, Mia Yang Ang, Emma Griffiths, Tengku Zetty Maztura Tengku Jamaluddin, Sheila Nathan and Hui-min Neoh 2024-10-21T15:46:21Z http://www.microbiologyresearch.org/content/journal/mgen/10.1099/mgen.0.000842?TRACK=RSS Plastics are inexpensive and widely used organic polymers, but their high durability hinders biodegradation. Polystyrene, including extruded polystyrene (also known as styrofoam), is among the most commonly produced plastics worldwide and is recalcitrant to microbial degradation. In this study, we assessed changes in the gut microbiome of superworms (Zophobas morio) reared on bran, polystyrene or under starvation conditions over a 3 weeks period. Superworms on all diets were able to complete their life cycle to pupae and imago, although superworms reared on polystyrene had minimal weight gains, resulting in lower pupation rates compared to bran reared worms. The change in microbial gut communities from baseline differed considerably between diet groups, with polystyrene and starvation groups characterized by a loss of microbial diversity and the presence of opportunistic pathogens. Inferred microbial functions enriched in the polystyrene group included transposon movements, membrane restructuring and adaptations to oxidative stress. We detected several encoded enzymes with reported polystyrene and styrene degradation abilities, supporting previous reports of polystyrene-degrading bacteria in the superworm gut. By recovering metagenome-assembled genomes (MAGs) we linked phylogeny and functions and identified genera including Pseudomonas , Rhodococcus and Corynebacterium that possess genes associated with polystyrene degradation. In conclusion, our results provide the first metagenomic insights into the metabolic pathways used by the gut microbiome of superworms to degrade polystyrene. Our results also confirm that superworms can survive on polystyrene feed, but this diet has considerable negative impacts on host gut microbiome diversity and health. Jiarui Sun, Apoorva Prabhu, Samuel T. N. Aroney and Christian Rinke 2022-06-09T13:23:25Z http://www.microbiologyresearch.org/content/journal/mgen/10.1099/mgen.0.001323?TRACK=RSS Mutations in the FUT2 gene that result in a lack of expression of histo-blood group antigens on secreted glycoproteins may shape the vaginal microbiota with consequences for birth outcome. To test this, we analysed the relationship between secretor status, vaginal microbiota and gestational length in an ethnically diverse cohort of 302 pregnant women, including 82 who delivered preterm. Lactobacillus gasseri and L. jensenii were found to have distinct co-occurrence patterns with other microbial taxa in non-secretors. Moreover, non-secretors with Lactobacillus spp. depleted high diversity vaginal microbiota in early pregnancy had significantly shorter gestational length than Lactobacillus spp. dominated non-secretors (mean of 241.54 days (sd=47.14) versus 266.21 (23.61); P-value=0.0251). Similar gestational length differences were observed between non-secretors with high vaginal diversity and secretors with Lactobacillus spp. dominance (mean of 262.52 days (SD=27.73); p-value=0.0439) or depletion (mean of 266.05 days (SD=20.81); p-value=0.0312). Our data highlight secretor status and blood-group antigen expression as being important mediators of vaginal microbiota–host interactions in the context of preterm birth risk. Samit Kundu, Gonçalo dos Santos Correia, Yun S. Lee, Sherrianne Ng, Lynne Sykes, Denise Chan, Holly Lewis, Richard G. Brown, Lindsay Kindinger, Anne Dell, Ten Feizi, Stuart M. Haslam, Yan Liu, Julian R. Marchesi, David A. MacIntyre and Phillip R. Bennett 2024-12-04T16:16:18Z http://www.microbiologyresearch.org/content/journal/mgen/10.1099/mgen.0.001318?TRACK=RSS Zoonotic pathogen transmission is of growing concern globally, with agricultural intensification facilitating interactions between humans, livestock and wild animals. Staphylococcus aureus is a major human pathogen, but it also causes mastitis in dairy cattle, leading to an economic burden on the dairy industry. Here, we investigated transmission within and between cattle and humans, including potential zoonotic transmission of S. aureus isolated from cattle and humans from three dairy farms and an associated primary school in New Zealand. Nasal swabs (N=170) were taken from healthy humans. Inguinal and combined nasal/inguinal swabs were taken from healthy cattle (N=1163). Whole-genome sequencing was performed for 96 S. aureus isolates (44 human and 52 cattle). Multilocus sequence typing and assessments of antimicrobial resistance and virulence were carried out. Potential within- and across-species transmission events were determined based on single nucleotide polymorphisms (SNPs). Thirteen potential transmission clusters were detected, with 12 clusters restricted to within-species and one potential zoonotic transmission cluster (ST5). Potential transmission among cattle was mostly limited to single age groups, likely because different age groups are managed separately on farms. While the prevalence of antimicrobial resistance (AMR) was low among both bovine and human isolates, the discovery of an extended-spectrum beta-lactamase gene (bla TEM-116) in a bovine isolate was concerning. This study provides evidence around frequency and patterns of potential transmission of S. aureus on dairy farms and highlights the AMR and virulence profile of asymptomatic carriage S. aureus isolates. Christina Straub, William Taylor, Nigel P. French, David R. Murdoch, Patricia Priest, Trevor Anderson and Pippa Scott 2024-12-04T16:17:31Z http://www.microbiologyresearch.org/content/journal/mgen/10.1099/mgen.0.001316?TRACK=RSS The reconstruction of complete bacterial genomes is essential for microbial research, offering insights into genetic content, ontology and regulation. While Pacific Biosciences (PacBio) provides high-quality genomes, its cost remains a limitation. Oxford Nanopore Technologies (ONT) offers long reads at a lower cost, yet its error rate raises scepticism. Recent ONT advancements, such as new Flow cells (R10.4.1), chemistry (V14) and duplex mode, improve data quality. Our study compares ONT with PacBio and Illumina, including hybrid data. We used Propionibacterium freudenreichii, a bacterium with a genome known for being difficult to reconstruct. By combining data from ONT’s Native Barcoding and a custom-developed BARSEQ method, we achieved high-quality, near-perfect genome assemblies. Our findings demonstrate, for the first time, that the combination of nanopore-only long-native with shorter PCR DNA reads (~3 kb) results in high-quality genome reconstruction, comparable to hybrid data assembly from two sequencing platforms. This endorses ONT as a cost-effective, stand-alone strategy for bacterial genome reconstruction. Additionally, we compared methylated motif detection between PacBio and ONT R10.4.1 data, showing that results comparable to PacBio are achievable using ONT, especially when utilizing the advanced Nanomotif tool. Axel Soto-Serrano, Wenwen Li, Farhad M. Panah, Yan Hui, Pablo Atienza, Alexey Fomenkov, Richard J. Roberts, Paulina Deptula and Lukasz Krych 2024-11-11T13:00:09Z http://www.microbiologyresearch.org/content/journal/mgen/10.1099/mgen.0.001312?TRACK=RSS Antimicrobial resistance (AMR) gene cassettes comprise an AMR gene flanked by short recombination sites (attI and attC or attC and attC). Integrons are genetic elements able to capture, excise and shuffle these cassettes, providing ‘adaptation on demand’, and can be found on both chromosomes and plasmids. Understanding the patterns of integron diversity may help to understand the epidemiology of AMR genes. As a case study, we examined the clinical resistance gene bla GES-5, an integron-associated class A carbapenemase first reported in Greece in 2004 and since observed worldwide, which to our knowledge has not been the subject of a previous global analysis. Using a dataset comprising all de-duplicated NCBI contigs containing bla GES-5 (n=104), we developed a pangenome graph-based workflow to characterize and cluster the diversity of bla GES-5-associated integrons. We demonstrate that bla GES-5-associated integrons on plasmids are different to those on chromosomes. Chromosomal integrons were almost all identified in Pseudomonas aeruginosa ST235, with a consistent gene cassette content and order. We observed instances where insertion sequence IS110 disrupted attC sites, which might immobilize the gene cassettes and explain the conserved integron structure despite the presence of intI1 integrase promoters, which would typically facilitate capture or excision and rearrangement. The plasmid-associated integrons were more diverse in their gene cassette content and order, which could be an indication of greater integrase activity and ‘shuffling’ of integrons on plasmids. William Matlock, Liam P. Shaw and Nicole Stoesser 2024-12-04T16:15:06Z http://www.microbiologyresearch.org/content/journal/mgen/10.1099/mgen.0.000409?TRACK=RSS Metagenomics and marker gene approaches, coupled with high-throughput sequencing technologies, have revolutionized the field of microbial ecology. Metagenomics is a culture-independent method that allows the identification and characterization of organisms from all kinds of samples. Whole-genome shotgun sequencing analyses the total DNA of a chosen sample to determine the presence of micro-organisms from all domains of life and their genomic content. Importantly, the whole-genome shotgun sequencing approach reveals the genomic diversity present, but can also give insights into the functional potential of the micro-organisms identified. The marker gene approach is based on the sequencing of a specific gene region. It allows one to describe the microbial composition based on the taxonomic groups present in the sample. It is frequently used to analyse the biodiversity of microbial ecosystems. Despite its importance, the analysis of metagenomic sequencing and marker gene data is quite a challenge. Here we review the primary workflows and software used for both approaches and discuss the current challenges in the field. Ana Elena Pérez-Cobas, Laura Gomez-Valero and Carmen Buchrieser 2020-07-24T15:08:51Z http://www.microbiologyresearch.org/content/journal/mgen/10.1099/mgen.0.001231?TRACK=RSS The ever-decreasing cost of sequencing and the growing potential applications of metagenomics have led to an unprecedented surge in data generation. One of the most prevalent applications of metagenomics is the study of microbial environments, such as the human gut. The gut microbiome plays a crucial role in human health, providing vital information for patient diagnosis and prognosis. However, analysing metagenomic data remains challenging due to several factors, including reference catalogues, sparsity and compositionality. Deep learning (DL) enables novel and promising approaches that complement state-of-the-art microbiome pipelines. DL-based methods can address almost all aspects of microbiome analysis, including novel pathogen detection, sequence classification, patient stratification and disease prediction. Beyond generating predictive models, a key aspect of these methods is also their interpretability. This article reviews DL approaches in metagenomics, including convolutional networks, autoencoders and attention-based models. These methods aggregate contextualized data and pave the way for improved patient care and a better understanding of the microbiome’s key role in our health. Gaspar Roy, Edi Prifti, Eugeni Belda and Jean-Daniel Zucker 2024-04-17T15:54:54Z