Yair Motro

Objective: Epidermolysis bullosa (EB) is a group of rare hereditary skin disorders characterized by the formation of painful blisters, erosions, and ulcers. In addition, the wounds can easily become infected with different pathogens. Therefore, the dynamics in the microbial populations across the various stages of EB can shed light on pathophysiology, the effect of treatment, and the factors involved in its recovery, but they are understudied. We thus sought to characterize the skin microbiome among patients with EB over time. Methods: A prospective study conducted in the pediatric dermatology clinic at Soroka Medical Center, Beer-Sheva, Israel. Children (0–18) with simplex and recessive dystrophic EB were sampled at two different time points: before a therapeutic regimen and 90 days (±14 days) later. Samples were obtained from lesional skin (wound), healthy, non-lesional skin, and seborrheic skin (forehead). Samples were subject to 16S rRNA amplicon sequencing. Analyses performed included comparisons of relative abundance at the phyla and genera taxonomic levels, alpha and beta diversity comparisons, and differential abundance. Results: 32 children with EB were enrolled, for whom 192 skin microbiome samples were obtained. Lesional skin samples harbored significantly less Bacteroidota and Fusobacteriota before the initiation of treatment. Following topical dressing, we observed more Firmicutes and less Proteobacteria in lesional skin samples than healthy and seborrheic skin samples. In addition, Staphylococcus was significantly more abundant in lesional samples than in non-lesional and seborrheic samples following treatment. Conclusions: Our study recaptured the reduced bacterial diversity and increased staphylococcal carriage in EB patients, showing a potential effect of topical dressing either directly on the wound microbiome or indirectly through the contribution towards skin healing. The detection of Firmicutes in general, and S. aureus specifically, commensurate with the application of a wound dressing may warrant the use of additional treatment methods to facilitate wound healing. Future studies in these patients should prospectively correlate the temporal changes in the microbiome associated with various treatment modalities in order to optimize the care of EB patients.

The de novo assembly of raw sequence data is key in metagenomic analysis. It allows recovering draft genomes from a pool of mixed raw reads, yielding longer sequences that offer contextual information and provide a more complete picture of the microbial community. To better compare de novo assemblers for metagenomic analysis, LMAS (Last Metagenomic Assembler Standing) was developed as a flexible platform allowing users to evaluate assembler performance given known standard communities. Overall, in our test datasets, k-mer De Bruijn graph assemblers outperformed the alternative approaches but came with a greater computational cost. Furthermore, assemblers branded as metagenomic specific did not consistently outperform other genomic assemblers in metagenomic samples. Some assemblers still in use, such as ABySS, MetaHipmer2, minia, and VelvetOptimiser, perform relatively poorly and should be used with caution when assembling complex samples. Meaningful strain resolution at the single-nucleotide polymorphism level was not achieved, even by the best assemblers tested. The choice of a de novo assembler depends on the computational resources available, the replicon of interest, and the major goals of the analysis. No single assembler appeared an ideal choice for short-read metagenomic prokaryote replicon assembly, each showing specific strengths. The choice of metagenomic assembler should be guided by user requirements and characteristics of the sample of interest, and LMAS provides an interactive evaluation platform for this purpose. LMAS is open source, and the workflow and its documentation are available at https://github.com/B-UMMI/LMAS and https://lmas.readthedocs.io/, respectively.

Dogs have a key role in law enforcement and military work, and research with the goal of improving working dog performance is ongoing. While there have been intriguing studies from lab animal models showing a potential connection between the gut microbiome and behavior or mental health there is a dearth of studies investigating the microbiome-behavior relationship in working dogs. The overall objective of this study was to characterize the microbiota of working dogs and to determine if the composition of the microbiota is associated with behavioral and performance outcomes. Freshly passed stools from each working canine (Total n = 134) were collected and subject to shotgun metagenomic sequencing using Illumina technology. Behavior, performance, and demographic metadata were collected. Descriptive statistics and prediction models of behavioral/phenotypic outcomes using gradient boosting classification based on Xgboost were used to study associations between the microbiome and outcomes. Regarding machine learning methodology, only microbiome features were used for training and predictors were estimated in cross-validation. Microbiome markers were statistically associated with motivation, aggression, cowardice/hesitation, sociability, obedience to one trainer vs many, and body condition score (BCS). When prediction models were developed based on machine learning, moderate predictive power was observed for motivation, sociability, and gastrointestinal issues. Findings from this study suggest potential gut microbiome markers of performance and could potentially advance care for working canines.

Extended-spectrum β-lactamases (ESBLs) are a growing public health threat, and one key human exposure point is through livestock and the food supply. Understanding microbiome factors associated with fecal ESBL carriage can help detect and ideally assist with controlling and preventing ESBL dissemination among livestock. The objective of this study was to investigate the diversity and composition of the heifer fecal microbiota in ESBL-producing Enterobacterales (ESBL-PE) carriers and noncarriers. A total of 59 fecal samples were collected from replacement heifers between 12 and 18 months old from eight dairy farms in central Israel. Genomic DNA was extracted, and 16S rRNA amplicon sequencing was performed (Illumina short reads), focusing on a comparison between 33 ESBL-PE carriers (55.9%) and 26 (44.1%) noncarriers. Samples were analyzed and compared using QIIME2 (DADA2 pipeline and taxonomic assignment with SILVA database) and associated R packages for alpha and beta diversity and taxonomic abundances. Alpha diversity (Shannon diversity) and beta diversity (unweighted UniFrac) showed no significant difference between ESBL-PE carriers and noncarriers. Heifers from farms feeding calves with pooled colostrum had higher ESBL-PE carriage rates than heifers from farms feeding with individual mother colostrum (p < 0.001). Taxonomical abundance analysis revealed that the most common bacterial phyla were Bacteroidetes (44%) and Firmicutes (38%). There was no significant difference in taxonomic composition between ESBL-PE carriers and noncarriers at the phylum and genus levels. However, LEfSe biomarker discovery analysis identified several genera which were significantly different between carriers and noncarriers. For example, Prevotellacaea, Bacteroides, Rikenellaceae, and uncultured Bacteroidales were more abundant in ESBL carriers than noncarriers. Some aspects of microbiota composition differ between ESBL carriers and noncarriers in dairy heifers, specifically the abundance of certain genera. Feeding with pooled colostrum may play a role in that assembly. These could potentially serve as markers of ESBL-PE carriage. However, further research is needed to determine whether these observed differences have a significant impact on colonization with ESBL-PE.

Brucella melitensis is a key etiological agent of brucellosis and has been increasingly subject to characterization using sequencing methodologies. This study aimed to investigate and compare short-read, long-read, and hybrid assemblies of B. melitensis. Eighteen B. melitensis isolates from Southern Israel were sequenced using Illumina and the Oxford Nanopore (ONP) MinION, and hybrid assemblies were generated with ONP long reads scaffolded on Illumina short reads. Short reads were assembled with INNUca with SPADes, long reads and hybrid with dragonflye. Abricate with the virulence factor database (VFDB) and in silico PCR (for the genes BetB, BPE275, BSPB, manA, mviN, omp19, perA, PrpA, VceC, and ureI) were used for identifying virulence genes, and a total of 61 virulence genes were identified in short-read, long-read, and hybrid assemblies of all 18 isolates. The phylogenetic analysis using long-read assemblies revealed several inconsistencies in cluster assignment as compared to using hybrid and short-read assemblies. Overall, hybrid assembly provided the most comprehensive data, and stand-alone short-read sequencing provided comparable data to stand-alone long-read sequencing regarding virulence genes. For genomic epidemiology studies, stand-alone ONP sequencing may require further refinement in order to be useful in endemic settings.

Brucellosis, a zoonosis mainly transmitted by consumption of unpasteurized dairy products, is endemic in Southern Israel, mainly among the Bedouin Arab population. However, the genomic epidemiology of B. melitensis in this region has not yet been elucidated. A cohort of brucellosis cases (n = 118) diagnosed between 2017–2019 was studied using whole-genome sequencing (WGS). Phylogenetic analyses utilized core genome MLST (cgMLST) for all local isolates and core genome SNPs for 347 human-associated B. melitensis genomes, including Israeli and publicly available sequences. Israeli isolates formed two main clusters, presenting a notable diversity, with no clear dominance of a specific strain. On a global scale, the Israeli genomes clustered according to their geographical location, in proximity to genomes originating from the Middle East, and formed the largest cluster in the tree, suggesting relatively high conservation. Our study unveils the genomic epidemiology of B. melitensis in Southern Israel, implicating that rather than a common source, the transmission pattern of brucellosis among Bedouin communities is complex, predominantly local, and household-based. Further, genomic surveillance of B. melitensis is expected to inform future public health and veterinary interventions and clinical care.

One anastomosis gastric bypass (OAGB) is an emerging bariatric procedure, yet data on its effect on the gastrointestinal tract are lacking. This study sought to evaluate the incidence of small-intestinal bacterial overgrowth (SIBO) following OAGB; explore its effect on nutritional, gastrointestinal, and weight outcomes; and assess post-OABG occurrence of pancreatic exocrine insufficiency (PEI) and altered gut microbiota composition. A prospective pilot cohort study of patients who underwent primary-OAGB surgery is here reported. The pre-surgical and 6-months-post-surgery measurements included anthropometrics, glucose breath-tests, biochemical tests, gastrointestinal symptoms, quality-of-life, dietary intake, and fecal sample collection. Thirty-two patients (50% females, 44.5 ± 12.3 years) participated in this study, and 29 attended the 6-month follow-up visit. The mean excess weight loss at 6 months post-OAGB was 67.8 ± 21.2%. The glucose breath-test was negative in all pre-surgery and positive in 37.0% at 6 months (p = 0.004). Positive glucose breath-test was associated with lower reported dietary intake and folate levels and higher vitamin A deficiency rates (p ≤ 0.036). Fecal elastase-1 test (FE1) was negative for all pre-surgery and positive in 26.1% at 6 months (p = 0.500). Both alpha and beta diversity decreased at 6 months post-surgery compared to pre-surgery (p ≤ 0.026). Relatively high incidences of SIBO and PEI were observed at 6 months post-OAGB, which may explain some gastrointestinal symptoms and nutritional deficiencies.

Brucellosis has a wide range of clinical severity in humans that remains poorly understood. Whole genome sequencing (WGS) analysis may be able to detect variation in virulence genes. We used Brucella melitensis sequences in the NCBI Sequence Read Archive (SRA) database to assemble 248 whole genomes, and additionally, assembled 27 B. melitensis genomes from samples of human patients in Southern Israel. We searched the 275 assembled genomes for the 43 B. melitensis virulence genes in the Virulence Factors of Pathogenic Bacteria Database (VFDB) and 10 other published putative virulence genes. We explored pan-genome variation across the genomes and in a pilot analysis, explored single nucleotide polymorphism (SNP) variation among the ten putative virulence genes. More than 99% of the genomes had sequences for all Brucella melitensis virulence genes included in the VFDB. The 10 other virulence genes of interest were present across all the genomes, but three of these genes had SNP variation associated with particular Brucella melitensis genotypes. SNP variation was also seen within the Israeli genomes obtained from a small geographic region. While the Brucella genome is highly conserved, this novel and large whole genome study of Brucella demonstrates the ability of whole genome and pan-genome analysis to screen multiple genomes and identify SNP variation in both known and novel virulence genes that could be associated with differential disease virulence. Further development of whole genome techniques and linkage with clinical metadata on disease outcomes could shed light on whether such variation in the Brucella genome plays a role in pathogenesis.

Antimicrobial resistance (AMR) in Helicobacter pylori is increasing and can result in treatment failure and inappropriate antibiotic usage. This study used whole genome sequencing (WGS) to comprehensively analyze the H. pylori resistome and phylogeny in order to characterize Israeli H. pylori. Israeli H. pylori isolates (n = 48) underwent antimicrobial susceptibility testing (AST) against five antimicrobials and WGS analysis. Literature review identified 111 mutations reported to correlate with phenotypic resistance to these antimicrobials. Analysis was conducted via our in-house bioinformatics pipeline targeting point mutations in the relevant genes (pbp1A, 23S rRNA, gyrA, rdxA, frxA, and rpoB) in order to assess genotype-to-phenotype correlation. Resistance rates of study isolates were as follows: clarithromycin 54%, metronidazole 31%, amoxicillin 10%, rifampicin 4%, and levofloxacin 2%. Genotype-to-phenotype correlation was inconsistent; for every analyzed gene at least one phenotypically susceptible isolate was found to have a mutation previously associated with resistance. This was also observed regarding mutations commonly used in commercial kits to diagnose AMR in H. pylori cases. Furthermore, 11 novel point mutations associated with a resistant phenotype were detected. Analysis of a unique set of H. pylori isolates demonstrates that inferring resistance phenotypes from WGS in H. pylori remains challenging and should be optimized further.