Competitive inhibition and mutualistic growth in co-infections: deciphering Staphylococcus aureus-Acinetobacter baumannii interaction dynamics.

Staphylococcus aureus (Sa) and Acinetobacter baumannii (Ab) are frequently co-isolated from polymicrobial infections that are severe and refractory to therapy. Here, we apply a combination of wet-lab experiments and in silico modeling to unveil the intricate nature of the Ab/Sa interaction using both, representative laboratory strains and strains co-isolated from clinical samples. This comprehensive methodology allowed uncovering Sa's capability to exert a partial interference on Ab by the expression of phenol-soluble modulins. In addition, we observed a cross-feeding mechanism by which Sa supports the growth of Ab by providing acetoin as an alternative carbon source. This study is the first to dissect the Ab/Sa interaction dynamics wherein competitive and cooperative strategies can intertwine. Through our findings, we illuminate the ecological mechanisms supporting their coexistence in the context of polymicrobial infections. Our research not only enriches our understanding but also opens doors to potential therapeutic avenues in managing these challenging infections.

Surveying the welfare of farmed fish species on a global scale through the fair-fish database.

Fish welfare is a critical issue that needs to be addressed by the rapidly growing aquaculture industry. Scientific knowledge regarding the natural behaviors of species and the conditions in which they are kept in farms is essential for improving their welfare in aquaculture. To provide a consistent overview of the welfare of farmed fish, the organization fair-fish has created the online platform fair-fish database, which gathers ethological knowledge categorized into profiles of farmed aquatic species. The WelfareChecks on this platform are profiles based on criteria that are rated based on the likelihood and potential of the species to experience a high level of welfare in aquaculture systems, together with the certainty about the findings. A score (WelfareScore) is calculated from these ratings, serving as a reference to identify knowledge gaps, assess welfare, and suggest ways to improve it. Here, we performed an in-depth analysis of the species with WelfareChecks already published in the fair-fish database based on their respective WelfareScores. In general, although just a small percentage of farmed aquatic species (~5%) have at least a 20% chance of experiencing a good level of welfare under minimal aquaculture conditions, 60% of them have at least some potential to achieve good welfare under high-standard conditions, with more than a third of the species (~37%) having at least a 20% potential. Despite that, several species exhibit a very high frequency of low chances and potential for experiencing good welfare levels under aquaculture conditions, besides a low degree of certainty based on literature reviews. Furthermore, many others show a very frequent occurrence of unclear or nonexistent knowledge in their profiles. The current welfare state is therefore poor for the majority of farmed aquatic species; yet, there is considerable potential for improvement. However, many species are very unlikely to achieve good welfare, even under high-standard conditions. Importantly, large knowledge gaps remain for an accurate assessment of the welfare of several farmed species.

Cactus species and tree forage hay in the diet of dairy goats.

The purpose of this study was to evaluate the influence of the association of Opuntia stricta (OS) or Nopalea cochenillifera (NC) with Moringa hay (MY) or Leucaena hay (LY) on nutrient intake, ingestive behavior, serum biochemistry, and milk production and composition of dairy goat. Eight multiparous Saanen goats were used, with an average of 68 ± 8 days in milk and 48.5 ± 6 kg of initial weight, fed with the following treatment diets: OS + MY; OS + LY; NC + MY, and NC + LY. The treatments were distributed in a double Latin square, in a 2 × 2 factorial scheme (two varieties of cactus and two of hay). Goats fed with NC had higher (P < 0.05) intakes of dry matter, crude protein, neutral detergent fiber (NDF), and non-fibrous carbohydrates. There was no influence (P > 0.05) on milk production, but goats fed with OS produced milk with higher (P < 0.05) fat content and presented higher (P < 0.05) feed efficiency. There was no effect (P > 0.05) of the hay type on the nutrient intake and milk production and composition of goats, but the animals fed with MY had higher (P < 0.05) serum cholesterol levels and greater efficiency of NDF rumination. Goats fed with OS showed greater feeding and rumination efficiency. Our results indicated that both cactus species could be successfully included in the diet of low yielding dairy goats fed 18.4% concentrate.

Genome-centric analyses of 165 metagenomes show that mobile genetic elements are crucial for the transmission of antimicrobial resistance genes to pathogens in activated sludge and wastewater.

Wastewater is considered a reservoir of antimicrobial resistance genes (ARGs), where the abundant antimicrobial-resistant bacteria and mobile genetic elements facilitate horizontal gene transfer. However, the prevalence and extent of these phenomena in different taxonomic groups that inhabit wastewater are still not fully understood. Here, we determined the presence of ARGs in metagenome-assembled genomes (MAGs) and evaluated the risks of MAG-carrying ARGs in potential human pathogens. The potential of these ARGs to be transmitted horizontally or vertically was also determined. A total of 5,916 MAGs (completeness >50%, contamination <10%) were recovered, covering 68 phyla and 279 genera. MAGs were dereplicated into 1,204 genome operational taxonomic units (gOTUs) as a proxy for species ( average nucleotide identity >0.95). The dominant ARG classes detected were bacitracin, multi-drug, macrolide-lincosamide-streptogramin (MLS), glycopeptide, and aminoglycoside, and 10.26% of them were located on plasmids. The main hosts of ARGs belonged to Escherichia, Klebsiella, Acinetobacter, Gresbergeria, Mycobacterium, and Thauera. Our data showed that 253 MAGs carried virulence factor genes (VFGs) divided into 44 gOTUs, of which 45 MAGs were carriers of ARGs, indicating that potential human pathogens carried ARGs. Alarmingly, the MAG assigned as Escherichia coli contained 159 VFGs, of which 95 were located on chromosomes and 10 on plasmids. In addition to shedding light on the prevalence of ARGs in individual genomes recovered from activated sludge and wastewater, our study demonstrates a workflow that can identify antimicrobial-resistant pathogens in complex microbial communities. IMPORTANCE: Antimicrobial resistance (AMR) threatens the health of humans, animals, and natural ecosystems. In our study, an analysis of 165 metagenomes from wastewater revealed antibiotic-targeted alteration, efflux, and inactivation as the most prevalent AMR mechanisms. We identified several genera correlated with multiple ARGs, including Klebsiella, Escherichia, Acinetobacter, Nitrospira, Ottowia, Pseudomonas, and Thauera, which could have significant implications for AMR transmission. The abundance of bacA, mexL, and aph(3")-I in the genomes calls for their urgent management in wastewater. Our approach could be applied to different ecosystems to assess the risk of potential pathogens containing ARGs. Our findings highlight the importance of managing AMR in wastewater and can help design measures to reduce the transmission and evolution of AMR in these systems.

MuDoGeR: Multi-Domain Genome recovery from metagenomes made easy.

Several computational frameworks and workflows that recover genomes from prokaryotes, eukaryotes and viruses from metagenomes exist. Yet, it is difficult for scientists with little bioinformatics experience to evaluate quality, annotate genes, dereplicate, assign taxonomy and calculate relative abundance and coverage of genomes belonging to different domains. MuDoGeR is a user-friendly tool tailored for those familiar with Unix command-line environment that makes it easy to recover genomes of prokaryotes, eukaryotes and viruses from metagenomes, either alone or in combination. We tested MuDoGeR using 24 individual-isolated genomes and 574 metagenomes, demonstrating the applicability for a few samples and high throughput. While MuDoGeR can recover eukaryotic viral sequences, its characterization is predominantly skewed towards bacterial and archaeal viruses, reflecting the field's current state. However, acting as a dynamic wrapper, the MuDoGeR is designed to constantly incorporate updates and integrate new tools, ensuring its ongoing relevance in the rapidly evolving field. MuDoGeR is open-source software available at https://github.com/mdsufz/MuDoGeR. Additionally, MuDoGeR is also available as a Singularity container.

The AnimalAssociatedMetagenomeDB reveals a bias towards livestock and developed countries and blind spots in functional-potential studies of animal-associated microbiomes.

BACKGROUND: Metagenomic data can shed light on animal-microbiome relationships and the functional potential of these communities. Over the past years, the generation of metagenomics data has increased exponentially, and so has the availability and reusability of data present in public repositories. However, identifying which datasets and associated metadata are available is not straightforward. We created the Animal-Associated Metagenome Metadata Database (AnimalAssociatedMetagenomeDB - AAMDB) to facilitate the identification and reuse of publicly available non-human, animal-associated metagenomic data, and metadata. Further, we used the AAMDB to (i) annotate common and scientific names of the species; (ii) determine the fraction of vertebrates and invertebrates; (iii) study their biogeography; and (iv) specify whether the animals were wild, pets, livestock or used for medical research. RESULTS: We manually selected metagenomes associated with non-human animals from SRA and MG-RAST.  Next, we standardized and curated 51 metadata attributes (e.g., host, compartment, geographic coordinates, and country). The AAMDB version 1.0 contains 10,885 metagenomes associated with 165 different species from 65 different countries. From the collected metagenomes, 51.1% were recovered from animals associated with medical research or grown for human consumption (i.e., mice, rats, cattle, pigs, and poultry). Further, we observed an over-representation of animals collected in temperate regions (89.2%) and a lower representation of samples from the polar zones, with only 11 samples in total. The most common genus among invertebrate animals was Trichocerca (rotifers). CONCLUSION: Our work may guide host species selection in novel animal-associated metagenome research, especially in biodiversity and conservation studies. The data available in our database will allow scientists to perform meta-analyses and test new hypotheses (e.g., host-specificity, strain heterogeneity, and biogeography of animal-associated metagenomes), leveraging existing data. The AAMDB WebApp is a user-friendly interface that is publicly available at https://webapp.ufz.de/aamdb/ .

Improved recovery and annotation of genes in metagenomes through the prediction of fungal introns.

Metagenomics provides a tool to assess the functional potential of environmental and host-associated microbiomes based on the analysis of environmental DNA: assembly, gene prediction and annotation. While gene prediction is straightforward for most bacterial and archaeal taxa, it has limited applicability in the majority of eukaryotic organisms, including fungi that contain introns in gene coding sequences. As a consequence, eukaryotic genes are underrepresented in metagenomics datasets and our understanding of the contribution of fungi and other eukaryotes to microbiome functioning is limited. Here, we developed a machine intelligence-based algorithm that predicts fungal introns in environmental DNA with reasonable precision and used it to improve the annotation of environmental metagenomes. Intron removal increased the number of predicted genes by up to 9.1% and improved the annotation of several others. The proportion of newly predicted genes increased with the share of eukaryotic genes in the metagenome and-within fungal taxa-increased with the number of introns per gene. Our approach provides a tool named SVMmycointron for improved metagenome annotation, especially of microbiomes with a high proportion of eukaryotes. The scripts described in the paper are made publicly available and can be readily utilized by microbiome researchers analysing metagenomics data.

Recovery of 197 eukaryotic bins reveals major challenges for eukaryote genome reconstruction from terrestrial metagenomes.

As most eukaryotic genomes are yet to be sequenced, the mechanisms underlying their contribution to different ecosystem processes remain untapped. Although approaches to recovering Prokaryotic genomes have become common in genome biology, few studies have tackled the recovery of eukaryotic genomes from metagenomes. This study assessed the reconstruction of microbial eukaryotic genomes using 6000 metagenomes from terrestrial and some transition environments using the EukRep pipeline. Only 215 metagenomic libraries yielded eukaryotic bins. From a total of 447 eukaryotic bins recovered 197 were classified at the phylum level. Streptophytes and fungi were the most represented clades with 83 and 73 bins, respectively. More than 78% of the obtained eukaryotic bins were recovered from samples whose biomes were classified as host-associated, aquatic, and anthropogenic terrestrial. However, only 93 bins were taxonomically assigned at the genus level and 17 bins at the species level. Completeness and contamination estimates were obtained for a total of 193 bins and consisted of 44.64% (σ = 27.41%) and 3.97% (σ = 6.53%), respectively. Micromonas commoda was the most frequent taxon found while Saccharomyces cerevisiae presented the highest completeness, probably because more reference genomes are available. Current measures of completeness are based on the presence of single-copy genes. However, mapping of the contigs from the recovered eukaryotic bins to the chromosomes of the reference genomes showed many gaps, suggesting that completeness measures should also include chromosome coverage. Recovering eukaryotic genomes will benefit significantly from long-read sequencing, development of tools for dealing with repeat-rich genomes, and improved reference genomes databases.

Metagenome-assembled genomes indicate that antimicrobial resistance genes are highly prevalent among urban bacteria and multidrug and glycopeptide resistances are ubiquitous in most taxa.

Introduction: Every year, millions of deaths are associated with the increased spread of antimicrobial resistance genes (ARGs) in bacteria. With the increasing urbanization of the global population, the spread of ARGs in urban bacteria has become a more severe threat to human health. Methods: In this study, we used metagenome-assembled genomes (MAGs) recovered from 1,153 urban metagenomes in multiple urban locations to investigate the fate and occurrence of ARGs in urban bacteria. Additionally, we analyzed the occurrence of these ARGs on plasmids and estimated the virulence of the bacterial species. Results: Our results showed that multidrug and glycopeptide ARGs are ubiquitous among urban bacteria. Additionally, we analyzed the deterministic effects of phylogeny on the spread of these ARGs and found ARG classes that have a non-random distribution within the phylogeny of our recovered MAGs. However, few ARGs were found on plasmids and most of the recovered MAGs contained few virulence factors. Discussion: Our results suggest that the observed non-random spreads of ARGs are not due to the transfer of plasmids and that most of the bacteria observed in the study are unlikely to be virulent. Additional research is needed to evaluate whether the ubiquitous and widespread ARG classes will become entirely prevalent among urban bacteria and how they spread among phylogenetically distinct species.

Combining Flow Cytometry and Metagenomics Improves Recovery of Metagenome-Assembled Genomes in a Cell Culture from Activated Sludge.

The recovery of metagenome-assembled genomes is biased towards the most abundant species in a given community. To improve the identification of species, even if only dominant species are recovered, we investigated the integration of flow cytometry cell sorting with bioinformatics tools to recover metagenome-assembled genomes. We used a cell culture of a wastewater microbial community as our model system. Cells were separated based on fluorescence signals via flow cytometry cell sorting into sub-communities: dominant gates, low abundant gates, and outer gates into subsets of the original community. Metagenome sequencing was performed for all groups. The unsorted community was used as control. We recovered a total of 24 metagenome-assembled genomes (MAGs) representing 11 species-level genome operational taxonomic units (gOTUs). In addition, 57 ribosomal operational taxonomic units (rOTUs) affiliated with 29 taxa at species level were reconstructed from metagenomic libraries. Our approach suggests a two-fold increase in the resolution when comparing sorted and unsorted communities. Our results also indicate that species abundance is one determinant of genome recovery from metagenomes as we can recover taxa in the sorted libraries that are not present in the unsorted community. In conclusion, a combination of cell sorting and metagenomics allows the recovery of MAGs undetected without cell sorting.

MarineMetagenomeDB: a public repository for curated and standardized metadata for marine metagenomes.

BACKGROUND: Metagenomics is an expanding field within microbial ecology, microbiology, and related disciplines. The number of metagenomes deposited in major public repositories such as Sequence Read Archive (SRA) and Metagenomic Rapid Annotations using Subsystems Technology (MG-RAST) is rising exponentially. However, data mining and interpretation can be challenging due to mis-annotated and misleading metadata entries. In this study, we describe the Marine Metagenome Metadata Database (MarineMetagenomeDB) to help researchers identify marine metagenomes of interest for re-analysis and meta-analysis. To this end, we have manually curated the associated metadata of several thousands of microbial metagenomes currently deposited at SRA and MG-RAST. RESULTS: In total, 125 terms were curated according to 17 different classes (e.g., biome, material, oceanic zone, geographic feature and oceanographic phenomena). Other standardized features include sample attributes (e.g., salinity, depth), sample location (e.g., latitude, longitude), and sequencing features (e.g., sequencing platform, sequence count). MarineMetagenomeDB version 1.0 contains 11,449 marine metagenomes from SRA and MG-RAST distributed across all oceans and several seas. Most samples were sequenced using Illumina sequencing technology (84.33%). More than 55% of the samples were collected from the Pacific and the Atlantic Oceans. About 40% of the samples had their biomes assigned as 'ocean'. The 'Quick Search' and 'Advanced Search' tabs allow users to use different filters to select samples of interest dynamically in the web app. The interactive map allows the visualization of samples based on their location on the world map. The web app is also equipped with a novel download tool (on both Windows and Linux operating systems), that allows easy download of raw sequence data of selected samples from their respective repositories. As a use case, we demonstrated how to use the MarineMetagenomeDB web app to select estuarine metagenomes for potential large-scale microbial biogeography studies. CONCLUSION: The MarineMetagenomeDB is a powerful resource for non-bioinformaticians to find marine metagenome samples with curated metadata and stimulate meta-studies involving marine microbiomes. Our user-friendly web app is publicly available at https://webapp.ufz.de/marmdb/ .

Machine learning-assisted identification of bioindicators predicts medium-chain carboxylate production performance of an anaerobic mixed culture.

BACKGROUND: The ability to quantitatively predict ecophysiological functions of microbial communities provides an important step to engineer microbiota for desired functions related to specific biochemical conversions. Here, we present the quantitative prediction of medium-chain carboxylate production in two continuous anaerobic bioreactors from 16S rRNA gene dynamics in enriched communities. RESULTS: By progressively shortening the hydraulic retention time (HRT) from 8 to 2 days with different temporal schemes in two bioreactors operated for 211 days, we achieved higher productivities and yields of the target products n-caproate and n-caprylate. The datasets generated from each bioreactor were applied independently for training and testing machine learning algorithms using 16S rRNA genes to predict n-caproate and n-caprylate productivities. Our dataset consisted of 14 and 40 samples from HRT of 8 and 2 days, respectively. Because of the size and balance of our dataset, we compared linear regression, support vector machine and random forest regression algorithms using the original and balanced datasets generated using synthetic minority oversampling. Further, we performed cross-validation to estimate model stability. The random forest regression was the best algorithm producing more consistent results with median of error rates below 8%. More than 90% accuracy in the prediction of n-caproate and n-caprylate productivities was achieved. Four inferred bioindicators belonging to the genera Olsenella, Lactobacillus, Syntrophococcus and Clostridium IV suggest their relevance to the higher carboxylate productivity at shorter HRT. The recovery of metagenome-assembled genomes of these bioindicators confirmed their genetic potential to perform key steps of medium-chain carboxylate production. CONCLUSIONS: Shortening the hydraulic retention time of the continuous bioreactor systems allows to shape the communities with desired chain elongation functions. Using machine learning, we demonstrated that 16S rRNA amplicon sequencing data can be used to predict bioreactor process performance quantitatively and accurately. Characterizing and harnessing bioindicators holds promise to manage reactor microbiota towards selection of the target processes. Our mathematical framework is transferrable to other ecosystem processes and microbial systems where community dynamics is linked to key functions. The general methodology used here can be adapted to data types of other functional categories such as genes, transcripts, proteins or metabolites. Video Abstract.

PredicTF: prediction of bacterial transcription factors in complex microbial communities using deep learning.

BACKGROUND: Transcription factors (TFs) are proteins controlling the flow of genetic information by regulating cellular gene expression. A better understanding of TFs in a bacterial community context may open novel revenues for exploring gene regulation in ecosystems where bacteria play a key role. Here we describe PredicTF, a platform supporting the prediction and classification of novel bacterial TF in single species and complex microbial communities. PredicTF is based on a deep learning algorithm. RESULTS: To train PredicTF, we created a TF database (BacTFDB) by manually curating a total of 11,961 TF distributed in 99 TF families. Five model organisms were used to test the performance and the accuracy of PredicTF. PredicTF was able to identify 24-62% of the known TFs with an average precision of 88% in our five model organisms. We demonstrated PredicTF using pure cultures and a complex microbial community. In these demonstrations, we used (meta)genomes for TF prediction and (meta)transcriptomes for determining the expression of putative TFs. CONCLUSION: PredicTF demonstrated high accuracy in predicting transcription factors in model organisms. We prepared the pipeline to be easily implemented in studies profiling TFs using (meta)genomes and (meta)transcriptomes. PredicTF is an open-source software available at https://github.com/mdsufz/PredicTF .

[Demographic and Professional Characteristics of Specialists in Obstetrics and Gynecology Registered in Portugal: Needs, Resources and Challenges]. / Características Demográficas e Profissionais dos Especialistas em Ginecologia-Obstetrícia Registados em Portugal: Necessidades, Recursos e Desafios.

INTRODUCTION: The demographic and professional characteristics of specialists in Obstetrics and Gynecology registered in Portugal are presented and current and future needs assessed. MATERIAL AND METHODS: An analysis of the data from Instituto Nacional de Estatística, Ordem dos Médicos and a survey sent to the directors of the departments of Obstetrics and Gynecology of Portuguese hospitals was perfomed. In order to calculate the necessary number of specialists, established indicators of the activity of the specialty were used. RESULTS: In 2018, there were 1 437 441 consultations of Obstetrics and Gynecology, 89 110 major gynecologic surgeries and 85 604 deliveries. For that, 1065 Obstetrics and Gynecology physicians, working 40 hours per week, with no more than 40% aged 55 years of age and older or including 30 residents per year, are deemed necessary. According to the National Institute of Statistics, in the same year there were 1143 specialists in Portuguese hospitals, of which 234 worked in private hospitals. On the other hand, 1772 specialists were registered with the Ordem dos Médicos: 1163 (66%) were aged 55 years old or above and 84% of specialists under the age of 40 were females. In 2020, there were 864 specialists, 46% of which aged years of age and older working in 39 out of the 41 public or public-private departments that answered the survey. In 2035, an increase of 7% in the required number of specialists is expected. CONCLUSION: In Portugal, there is not lack of Obstetrics and Gynecology specialists in absolute numbers, but the large number of specialists aged 55 years of age and older, who are exempt from shifts in emergency department work, and the existence of regional asymmetries contribute to the perpetuation of some shortages of these healthcare professionals in several departments, namely in public hospitals.

Introdução: Apresentam-se as caraterísticas demográficas e profissionais dos especialistas de Ginecologia-Obstetrícia registados em Portugal e avaliam-se necessidades atuais e futuras.Material e Métodos: Analisaram-se dados do Instituto Nacional de Estatística, da Ordem dos Médicos e de resposta a questionário enviado a diretores de serviços hospitalares portugueses de Ginecologia-Obstetrícia. Calcularam-se as necessidades de especialistas com base em indicadores estabelecidos de atividade médica da especialidade.Resultados: Em 2018, registaram-se, em Portugal, 1 437 441 consultas da especialidade, 89 110 grandes cirurgias e 85 604 partos. Para essa atividade calcula-se serem necessários 1065 médicos da especialidade, em regime de 40 horas semanais, dos quais não mais do que 40% com idade igual ou superior a 55 anos; para manter este número são necessários 30 internos por ano. Segundo o Instituto Nacional de Estatística, nesse ano existiam 1143 especialistas nos hospitais portugueses, 234 dos quais em hospitais privados. Por outro lado, estavam inscritos 1772 especialistas na Ordem dos Médicos, dos quais 1163 (66%) apresentavam uma idade igual ou superior a 55 anos, sendo 84% dos especialistas com menos de 40 anos do sexo feminino. Em 2020, nos 39 dos 41 serviços públicos e público-privados que responderam ao questionário, existiam 864 especialistas, dos quais 395 (46%) com idade igual ou superior a 55 anos. Para 2035 prevê-se um aumento de 7% nas necessidades de especialistas desta área.Conclusão: Em Portugal não há falta de especialistas de Ginecologia-Obstetrícia em número absoluto, mas a existência de um elevado número de especialistas com idade igual ou superior a 55 anos, que tem direito a deixar de prestar atividade nos Serviços de Urgência, e de assimetrias regionais, contribuem para que continuem a existir algumas carências destes profissionais em vários serviços, nomeadamente em hospitais públicos.

Vestibular Schwannoma Leading to Contacting Aneurysm Rupture: An Unusual Presentation.

Subarachnoid hemorrhage (SAH) is a rare manifestation of brain tumors, being even rarer in vestibular schwannomas. We report the second case of a posterior circulation aneurysm close to the tumor capsule, responsible for SAH as an initial manifestation of a vestibular schwannoma. A 67-year-old female was admitted to the Emergency Department with sudden onset of nausea and headache. A diagnosis of a SAH and a tumor of the right cerebellopontine angle was made. An angiography showed an aneurysm in the dependency of the right anterior inferior cerebellar artery (AICA), juxtaposed to the tumor capsule. The patient underwent surgery, the tumor was removed, and the aneurysm was treated. This case highlights that SAH in patients with vestibular schwannoma may originate from a contact aneurysm. Although exceedingly rare, surgeons should consider this scenario in vestibular schwannoma presenting with SAH, and angiography is important for its diagnosis.

OrtSuite: from genomes to prediction of microbial interactions within targeted ecosystem processes.

The high complexity found in microbial communities makes the identification of microbial interactions challenging. To address this challenge, we present OrtSuite, a flexible workflow to predict putative microbial interactions based on genomic content of microbial communities and targeted to specific ecosystem processes. The pipeline is composed of three user-friendly bash commands. OrtSuite combines ortholog clustering with genome annotation strategies limited to user-defined sets of functions allowing for hypothesis-driven data analysis such as assessing microbial interactions in specific ecosystems. OrtSuite matched, on average, 96% of experimentally verified KEGG orthologs involved in benzoate degradation in a known group of benzoate degraders. We evaluated the identification of putative synergistic species interactions using the sequenced genomes of an independent study that had previously proposed potential species interactions in benzoate degradation. OrtSuite is an easy-to-use workflow that allows for rapid functional annotation based on a user-curated database and can easily be extended to ecosystem processes where connections between genes and reactions are known. OrtSuite is an open-source software available at https://github.com/mdsufz/OrtSuite.

Metagenomes, metatranscriptomes and microbiomes of naturally decomposing deadwood.

Deadwood represents significant carbon (C) stock in a temperate forests. Its decomposition and C mobilization is accomplished by decomposer microorganisms - fungi and bacteria - who also supply the foodweb of commensalist microbes. Due to the ecosystem-level importance of deadwood habitat as a C and nutrient stock with significant nitrogen fixation, the deadwood microbiome composition and function are critical to understanding the microbial processes related to its decomposition. We present a comprehensive suite of data packages obtained through environmental DNA and RNA sequencing from natural deadwood. Data provide a complex picture of the composition and function of microbiome on decomposing trunks of European beech (Fagus sylvatica L.) in a natural forest. Packages include deadwood metagenomes, metatranscriptomes, sequences of total RNA, bacterial genomes resolved from metagenomic data and the 16S rRNA gene and ITS2 metabarcoding markers to characterize the bacterial and fungal communities. This project will be of use to microbiologists, environmental biologists and biogeochemists interested in the microbial processes associated with the transformation of recalcitrant plant biomass.

Punch shear test for quantitative evaluation of bone defect repair in Wistar rat tibia.

INTRODUCTION: Bone healing is a complex process influenced by biological and mechanical factors that restores the injured bone's load bearing function. Qualitative methods are usually employed to assess this repair process. This study presents a method of quantitative evaluation of bone repair in circular defects produced in the medial proximal metaphysis of the tibia of rats by means of punch shear tests (PST). OBJECTIVE: To describe and test a mechanical punch shear test designed to quantify over time the regeneration of bone defects produced in Wistar rats' tibiae. MATERIAL AND METHODS: In seven experimental groups, 3.2 mm in diameter and 1.5 mm deep defects were drilled on the medial surface of both proximal tibial metaphyses of the animals, just below the joint surfaces. The animals of an additional group were maintained with intact tibiae. After one, two, three, four, six, eight and 12 weeks of follow-up, the animals were sacrificed and the tibiae removed. After removing the soft tissue, the tibial proximal metaphyses were embedded in epoxy resin and cut with a diamond cutting blade, in order to obtain bone slices with equal thickness. The PST were carried out in a universal testing machine and the maximum shear forces were measured. RESULTS: The forces increased as a function of the follow-up time in the period of one to three weeks (p <0.001); from this follow-up time on, there were no statistical significant differences between the groups, including the intact tibiae. CONCLUSION: The test method proved to be suitable to quantitatively assess bone regeneration in monocortical defects produced in the proximal metaphysis of rat tibia within one and three weeks after defect production.

Mining Synergistic Microbial Interactions: A Roadmap on How to Integrate Multi-Omics Data.

Mining interspecies interactions remain a challenge due to the complex nature of microbial communities and the need for computational power to handle big data. Our meta-analysis indicates that genetic potential alone does not resolve all issues involving mining of microbial interactions. Nevertheless, it can be used as the starting point to infer synergistic interspecies interactions and to limit the search space (i.e., number of species and metabolic reactions) to a manageable size. A reduced search space decreases the number of additional experiments necessary to validate the inferred putative interactions. As validation experiments, we examine how multi-omics and state of the art imaging techniques may further improve our understanding of species interactions' role in ecosystem processes. Finally, we analyze pros and cons from the current methods to infer microbial interactions from genetic potential and propose a new theoretical framework based on: (i) genomic information of key members of a community; (ii) information of ecosystem processes involved with a specific hypothesis or research question; (iii) the ability to identify putative species' contributions to ecosystem processes of interest; and, (iv) validation of putative microbial interactions through integration of other data sources.