Systems-Based Approach for Optimization of Assembly-Free Bacterial MLST Mapping

Epidemiological surveillance of bacterial pathogens requires real-time data analysis with a fast turnaround, while aiming at generating two main outcomes: (1) species-level identification and (2) variant mapping at different levels of genotypic resolution for population-based tracking and surveillance, in addition to predicting traits such as antimicrobial resistance (AMR). Multilocus sequence typing (MLST) aids this process by identifying sequence types (ST) based on seven ubiquitous genome-scattered loci. In this paper, we selected one assembly-dependent and one assembly-free method for ST mapping and applied them with the default settings and ST schemes they are distributed with, and systematically assessed their accuracy and scalability across a wide array of phylogenetically divergent Public Health-relevant bacterial pathogens with available MLST databases. Our data show that the optimal k-mer length for stringMLST is species-specific and that genome-intrinsic and -extrinsic features can affect the performance and accuracy of the program. Although suitable parameters could be identified for most organisms, there were instances where this program may not be directly deployable in its current format. Next, we integrated stringMLST into our freely available and scalable hierarchical-based population genomics platform, ProkEvo, and further demonstrated how the implementation facilitates automated, reproducible bacterial population analysis

ProkEvo: an automated, reproducible, and scalable framework for high-throughput bacterial population genomics analyses

Whole Genome Sequence (WGS) data from bacterial species is used for a variety of applications ranging from basic microbiological research, diagnostics, and epidemiological surveillance. The availability of WGS data from hundreds of thousands of individual isolates of individual microbial species poses a tremendous opportunity for discovery and hypothesis-generating research into ecology and evolution of these microorganisms. Flexibility, scalability, and user-friendliness of existing pipelines for population-scale inquiry, however, limit applications of systematic, population-scale approaches. Here, we present ProkEvo, an automated, scalable, reproducible, and open-source framework for bacterial population genomics analyses using WGS data. ProkEvo was specifically developed to achieve the following goals: (1) Automation and scaling of complex combinations of computational analyses for many thousands of bacterial genomes from inputs of raw Illumina paired-end sequence reads; (2) Use of workflow management systems (WMS) such as Pegasus WMS to ensure reproducibility, scalability, modularity, fault-tolerance, and robust file management throughout the process; (3) Use of high-performance and high-throughput computational platforms; (4) Generation of hierarchical-based population structure analysis based on combinations of multi-locus and Bayesian statistical approaches for classification for ecological and epidemiological inquiries; (5) Association of antimicrobial resistance (AMR) genes, putative virulence factors, and plasmids from curated databases with the hierarchically-related genotypic classifications; and (6) Production of pan-genome annotations and data compilation that can be utilized for downstream analysis such as identification of population-specific genomic signatures. The scalability of ProkEvo was measured with two datasets comprising significantly different numbers of input genomes (one with ~2,400 genomes, and the second with ~23,000 genomes). Depending on the dataset and the computational platform used, the running time of ProkEvo varied from ~3-26 days. ProkEvo can be used with virtually any bacterial species, and the Pegasus WMS uniquely facilitates addition or removal of programs from the workflow or modification of options within them. To demonstrate versatility of the ProkEvo platform, we performed a hierarchical-based population structure analyses from available genomes of three distinct pathogenic bacterial species as individual case studies. The specific case studies illustrate how hierarchical analyses of population structures, genotype frequencies, and distribution of specific gene functions can be integrated into an analysis. Collectively, our study shows that ProkEvo presents a practical viable option for scalable, automated analyses of bacterial populations with direct applications for basic microbiology research, clinical microbiological diagnostics, and epidemiological surveillance

Salmonella enterica induces biogeography-specific changes in the gut microbiome of pigs

Swine are a major reservoir of an array of zoonotic Salmonella enterica subsp. enterica lineage I serovars including Derby, Typhimurium, and 4,[5],12:i:- (a.k.a. Monophasic Typhimurium). In this study, we assessed the gastrointestinal (GI) microbiome composition of pigs in different intestinal compartments and the feces following infection with specific zoonotic serovars of S. enterica (S. Derby, S. Monophasic, and S. Typhimurium). 16S rRNA based microbiome analysis was performed to assess for GI microbiome changes in terms of diversity (alpha and beta), community structure and volatility, and specific taxa alterations across GI biogeography (small and large intestine, feces) and days post-infection (DPI) 2, 4, and 28; these results were compared to disease phenotypes measured as histopathological changes. As previously reported, only S. Monophasic and S. Typhimurium induced morphological alterations that marked an inflammatory milieu restricted to the large intestine in this experimental model. S. Typhimurium alone induced significant changes at the alpha- (Simpson’s and Shannon’s indexes) and beta-diversity levels, specifically at the peak of inflammation in the large intestine and feces. Increased community dispersion and volatility in colonic apex and fecal microbiomes were also noted for S. Typhimurium. All three Salmonella serovars altered community structure as measured by co-occurrence networks; this was most prominent at DPI 2 and 4 in colonic apex samples. At the genus taxonomic level, a diverse array of putative short-chain fatty acid (SCFA) producing bacteria were altered and often decreased during the peak of inflammation at DPI 2 and 4 within colonic apex and fecal samples. Among all putative SCFA producing bacteria, Prevotella showed a broad pattern of negative correlation with disease scores at the peak of inflammation. In addition, Prevotella 9 was found to be significantly reduced in all Salmonella infected groups compared to the control at DPI 4 in the colonic apex. In conclusion, this work further elucidates that distinct swine-related zoonotic serovars of S. enterica can induce both shared (high resilience) and unique (altered resistance) alterations in gut microbiome biogeography, which helps inform future investigations of dietary modifications aimed at increasing colonization resistance against Salmonella through GI microbiome alterations

Transversal study about acute acromioclavicular lesions

The objective of the present transversal study is to check how Brazilian orthopedists treat these injuries, their criteria for choosing the treatment, results and complications. METHODS: During the 6th Brazilian Congress of Shoulder and Elbow Surgery (CBOC) and the 38th Brazilian Congress of Orthopaedics and Traumatology (CBOT) 507 questionnaires were distributed (148 CBOC and 359 CBOT), with 478 being considered for analysis. RESULTS: Regarding type-I and -II ACIs, most of the respondents use traditional non-surgical methods. On the other hand, for type-IV, V and VI injuries, 475 (99.4%) of the respondents indicate surgical methods. Concerning type-III injuries, there is no consensus in the selection between traditional and surgical treatment for 386 (80.7%) respondents, with the most important factor for selecting a given treatment method being the patient's level of sports practice and age. CONCLUSION: There is no consensus regarding type-III ACIs, and the selection of the best treatment method is made according to patient's individual characteristics. However, current literature shows a trend towards non-operative methods.OBJETIVO: O objetivo do presente estudo transversal é verificar como o ortopedista brasileiro interpreta as lesões acromioclaviculares quanto aos critérios para a indicação do tratamento cirúrgico ou não, seus métodos preferidos, as complicações mais frequentes e os resultados obtidos. MÉTODOS: Durante o 6º Congresso Brasileiro de Cirurgia do Ombro e Cotovelo (CBOC) e o 38º Congresso Brasileiro de Ortopedia e Traumatologia (CBOT) foram distribuídos 507 questionários, sendo considerados 478 para análise. RESULTADOS: Em relação ao tratamento das LAC tipo I e II, a maioria dos entrevistados utilizam métodos não cirúrgicos. Em contraposição nas LAC IV, V e VI 475 (99,4%) dos entrevistados tratam essas lesões cirurgicamente. Nas LAC tipo III não existe uma definição na escolha do tratamento cirúrgico ou não cirúrgico para 386 (80,7%) entrevistados, sendo que o fator mais importante para tomada de decisão para a maioria dos entrevistados é a atividade esportiva do paciente e a idade. CONCLUSÃO: Nas LAC tipo III não há consenso, sendo o tratamento determinado conforme as características do paciente, contudo na literatura atual há uma tendência para o tratamento não cirúrgico destas lesões.Universidade Federal de São Paulo (UNIFESP) Departamento de Ortopedia e TraumatologiaUNIFESP, Depto. de Ortopedia e TraumatologiaSciEL

Heuristic and Hierarchical-Based Population Mining of Salmonella enterica Lineage I Pan-Genomes as a Platform to Enhance Food Safety

The recent incorporation of bacterial whole-genome sequencing (WGS) into Public Health laboratories has enhanced foodborne outbreak detection and source attribution. As a result, large volumes of publicly available datasets can be used to study the biology of foodborne pathogen populations at an unprecedented scale. To demonstrate the application of a heuristic and agnostic hierarchical population structure guided pan-genome enrichment analysis (PANGEA), we used populations of S. enterica lineage I to achieve two main objectives: (i) show how hierarchical population inquiry at different scales of resolution can enhance ecological and epidemiological inquiries; and (ii) identify population-specific inferable traits that could provide selective advantages in food production environments. Publicly available WGS data were obtained from NCBI database for three serovars of Salmonella enterica subsp. enterica lineage I (S. Typhimurium, S. Newport, and S. Infantis). Using the hierarchical genotypic classifications (Serovar, BAPS1, ST, cgMLST), datasets from each of the three serovars showed varying degrees of clonal structuring. When the accessory genome (PANGEA) was mapped onto these hierarchical structures, accessory loci could be linked with specific genotypes. A large heavy-metal resistance mobile element was found in the Monophasic ST34 lineage of S. Typhimurium, and laboratory testing showed that Monophasic isolates have on average a higher degree of copper resistance than the Biphasic ones. In S. Newport, an extra sugEgene copy was found among most isolates of the ST45 lineage, and laboratory testing of multiple isolates confirmed that isolates of S. Newport ST45 were on average less sensitive to the disinfectant cetylpyridimium chloride than non-ST45 isolates. Lastly, data-mining of the accessory genomic content of S. Infantis revealed two cryptic Ecotypes with distinct accessory genomic content and distinct ecological patterns. Poultry appears to be themajor reservoir for Ecotype 1, and temporal analysis further suggested a recent ecological succession, with Ecotype 2 apparently being displaced by Ecotype 1. Altogether, the use of a heuristic hierarchical-based population structure analysis that includes bacterial pan-genomes (core and accessory genomes) can (1) improve genomic resolution for mapping populations and accessing epidemiological patterns; and (2) define lineage-specific informative loci that may be associated with survival in the food chain

The tropical forest and fire emissions experiment: Trace gases emitted by smoldering logs and dung from deforestation and pasture fires in Brazil

Earlier work showed that Amazonian biomass burning produces both lofted and initially unlofted emissions in large amounts. A mobile, Fourier transform infrared spectrometer (FTIR) measured the unlofted emissions of 17 trace gases from residual smoldering combustion (RSC) of logs as part of the Tropical Forest and Fire Emissions Experiment (TROFFEE) during the 2004 Amazonian dry season. The RSC emissions were highly variable and the few earlier RSC measurements lay near the high end of combustion efficiency observed in this study. Fuel consumption by RSC was ∼5% of total for a planned deforestation fire. Much regional RSC probably occurs in the residual woody debris burned during pasture maintenance fires. RSC could increase estimated total fire emissions for the Amazon region by 20–50% for several important VOC. FTIR emissions measurements of burning dung (in a pasture) showed high emission ratios for acetic acid and ammonia to CO (6.6 ± 3.4% and 8.9 ± 2.1%). Large emissions of nitrogen containing trace gases from burning dung and crop waste could mean that biomass burning in India produces more particle mass than previously assumed. Measurements of late-stage kiln emissions suggested that VOC/CO may increase as carbonization is extended. A cook stove emitted many VOC and NH3 far outside the range observed for open wood cooking fires. Enclosed/vented cooking stoves may change the chemistry of the smoke that is emitted

Commensal \u3ci\u3eEscherichia coli\u3c/i\u3e Strains Can Promote Intestinal Inflammation via Differential Interleukin-6 Production

Escherichia coli is a facultative anaerobic symbiont found widely among mammalian gastrointestinal tracts. Several human studies have reported increased commensal E. coli abundance in the intestine during inflammation; however, host immunological responses toward commensal E. coli during inflammation are not well-defined. Here, we show that colonization of gnotobiotic mice with different genotypes of commensal E. coli isolated from healthy conventional microbiota mice and representing distinct populations of E. coli elicited strain-specific disease phenotypes and immunopathological changes following treatment with the inflammatory stimulus, dextran sulfate sodium (DSS). Production of the inflammatory cytokines GM-CSF, IL-6, and IFN-y was a hallmark of the severe inflammation induced by E. coli strains of Sequence Type 129 (ST129) and ST375 following DSS administration. In contrast, colonization with E. coli strains ST150 and ST468 caused mild intestinal inflammation and triggered only low levels of pro-inflammatory cytokines, a response indistinguishable from that of E. coli-free control mice treated with DSS. The disease development observed with ST129 and ST375 colonization was not directly associated with their abundance in the GI tract as their levels did not change throughout DSS treatment, and no major differences in bacterial burden in the gut were observed among the strains tested. Data mining and in vivo neutralization identified IL-6 as a key cytokine responsible for the observed differential disease severity. Collectively, our results show that the capacity to exacerbate acute intestinal inflammation is a strain-specific trait that can potentially be overcome by blocking the pro-inflammatory immune responses that mediate intestinal tissue damage

Patient-physician discordance in assessment of adherence to inhaled controller medication: a cross-sectional analysis of two cohorts

We aimed to compare patient's and physician's ratings of inhaled medication adherence and to identify predictors of patient-physician discordance.(SFRH/BPD/115169/2016) funded by Fundação para a Ciência e Tecnologia (FCT); ERDF (European Regional Development Fund) through the operations: POCI-01-0145-FEDER-029130 ('mINSPIRERS—mHealth to measure and improve adherence to medication in chronic obstructive respiratory diseases—generalisation and evaluation of gamification, peer support and advanced image processing technologies') cofunded by the COMPETE2020 (Programa Operacional Competitividade e Internacionalização), Portugal 2020 and by Portuguese Funds through FCT (Fundação para a Ciência e a Tecnologia).info:eu-repo/semantics/publishedVersio

Evidence for a Causal Role for \u3ci\u3eEscherichia coli\u3c/i\u3e Strains Identified as Adherent-Invasive (AIEC) in Intestinal Inflammation

Enrichment of adherent-invasive Escherichia coli (AIEC) has been consistently detected in subsets of inflammatory bowel disease (IBD) patients. Although some AIEC strains cause colitis in animal models, these studies did not systematically compare AIEC with non-AIEC strains, and causal links between AIEC and disease are still disputed. Specifically, it remains unclear whether AIEC shows enhanced pathogenicity compared to that of commensal E. coli found in the same ecological microhabitat and if the in vitro phenotypes used to classify strains as AIEC are pathologically relevant. Here, we utilized in vitro phenotyping and a murine model of intestinal inflammation to systematically compare strains identified as AIEC with those identified as non-AIEC and relate AIEC phenotypes to pathogenicity. Strains identified as AIEC caused, on average, more severe intestinal inflammation. Intracellular survival/replication phenotypes routinely used to classify AIEC positively correlated with disease, while adherence to epithelial cells and tumor necrosis factor alpha production by macrophages did not. This knowledge was then applied to design and test a strategy to prevent inflammation by selecting E. coli strains that adhered to epithelial cells but poorly survived/replicated intracellularly. Two E. coli strains that ameliorated AIEC-mediated disease were subsequently identified. In summary, our results show a relationship between intracellular survival/replication in E. coli and pathology in murine colitis, suggesting that strains possessing these phenotypes might not only become enriched in human IBD but also contribute to disease. We provide new evidence that specific AIEC phenotypes are pathologically relevant and proof of principle that such mechanistic information can be therapeutically exploited to alleviate intestinal inflammation