Biology subjects

Kaplan, S.

Publications and source records attributed to Kaplan, S..

4 recordsLinked to original sources

bioRxiv2022

Canine saliva is a source of interspecies antimicrobial resistance gene transfer

While the One Health issues of intensive animal farming are commonly discussed, keeping companion animals is less associated with the interspecies headway of antimicrobial resistance. With the constant advance of veterinary standards, antibiotics are regularly applied in companion animal medicine. Due to the close coexsistance of dogs and humans, dog bites and other casual encounters with dog saliva (e.g. licking the owner) are common. According to our metagenome studies based on 26 new generation sequencing canine saliva datasets from 2020 and 2021 reposited in NCBI SRA by The 10,000 Dog Genome Consortium and the Broad Institute within Darwins Ark project, canine saliva is rich in bacteria with predictably transferable antimicrobial resistance genes (ARGs). In the genom of potentially pathogenic Bacteroides, Capnocytophaga, Corynebacterium, Fusobacterium, Pasteurella, Porphyromonas, Staphylococcus and Streptococcus species, that are some of the most relevant bacteria in dog bite infections, ARGs against aminoglycosides, carbapenems, cephalosporins, glycylcyclines, lincosamides, macrolides, oxazolidinone, penams, phenicols, pleuromutilins, streptogramins, sulfonamides and tetracyclines could be identfied. Several ARGs, including ones against amoxicillin-clavulanate, the most commonly applied antibiotic by dog bites, was predicted to be potentially transferable based on their association with mobile genetic elements (e.g. plasmids, phages, integrated mobile genetic elements). According to our findings canine saliva may be a source of transfer of ARG-rich bacteria, that can either colonize the human body or transport ARGs to the host bacteriota and thus can be considered as a risk in the spread of antimicrobial resistance.

genomics↗

bioRxiv2022

Neurodevelopmental Patterns of Early Postnatal White Matter Maturation Represent Distinct Underlying Microstructure and Histology

During the early postnatal period, cerebral white matter undergoes rapid maturation through a complex series of interrelated cellular and histogenetic processes. Accurately quantifying these processes is important for improving understanding of early brain development, developmental abnormalities related to prematurity, and neurodevelopmental diseases. Past efforts have used magnetic resonance imaging (MRI) to track these developmental processes in vivo. However, most previous studies have relied on single imaging modality data and have often been limited by small samples and analytics that do not evaluate complex multivariate imaging patterns. Here, we applied an advanced unsupervised multivariate pattern analysis technique, non-negative matrix factorization (NMF), to T2w/T1w signal ratio maps from a large cohort of newborns (Developing Human Connectome Project [dHCP], n=342), revealing patterns of synchronous white matter maturation. These patterns showed divergent age-related maturational trajectories and differential susceptibility to premature birth, which were replicated in an independent large sample of newborns (Early Life Adversity, Biological Embedding, and Risk for Developmental Precursors of Mental Disorders [eLABE], n=239). Furthermore, we showed that T2w/T1w signal variations in white matter maturational patterns are explained by differential contributions of white matter microstructure indices (i.e., free water content and neurite density index) derived from neurite orientation dispersion and density imaging (NODDI) modeling of diffusion-weighted MRI. Finally, we demonstrated how white matter maturation patterns relate to distinct histological features by comparing our findings with postmortem late fetal/early postnatal brain tissue staining. Together, these results delineate a novel MRI representation of white matter microstructural and histological reorganization during the early postnatal development.

neuroscience↗

bioRxiv2021

Antimicrobial resistance determinants in silage

Animal products may play a role in developing and spreading antimicrobial resistance in several ways. On the one hand, residues of antibiotics not adequately used in animal farming can enter the human body via food. But resistant bacteria may also be present in animal products, which can transfer the antimicrobial resistance genes (ARG) to the bacteria in the consumers body by horizontal gene transfer. As previous studies have shown that fermented foods have a meaningful ARG content, it is indicated that such genes may also be present in silage used as mass feed in the cattle sector. In our study, we aspired to answer what ARGs occur in silage and what mobility characteristics they have? For this purpose, we have analyzed bioinformatically 52 freely available deep sequenced silage samples from shotgun metagenome next-generation sequencing. A total of 17 perfect matched ARGs occurred 55 times in the samples. More than half of these ARGs are mobile because they can be linked to integrative mobile genetic elements, prophages or plasmids. Our results point to a neglected but substantial ARG source in the food chain.

genomics↗

bioRxiv2021

Robotic Antimicrobial Susceptibility Platform (RASP): A Next Generation Approach to One-Health Surveillance of Antimicrobial Resistance.

BackgroundSurveillance of antimicrobial resistance (AMR) is critical to reducing its wide-reaching impact. Its reliance on sample size invites solutions to longstanding constraints regarding scalability. A robotic platform (RASP) was developed for high-throughput AMR surveillance in accordance with internationally recognised standards (CLSI and ISO 20776-1:2019) and validated through a series of experiments. MethodsExperiment A compared RASPs ability to achieve consistent MICs to that of a human technician across eight replicates for four E. coli isolates. Experiment B assessed RASPs agreement with human performed MICs across 91 E. coli isolates with a diverse range of AMR profiles. Additionally, to demonstrate its real-world applicability, the RASP workflow was then applied to five faecal samples where a minimum of 47 E. coli per animal (239 total) were evaluated using an AMR indexing framework. ResultsFor each drug-rater-isolate combination in experiment A, there was a clear consensus of the MIC and deviation from the consensus remained within one doubling-dilution (the exception being gentamicin at two dilutions). Experiment B revealed a concordance correlation coefficient of 0.9670 (95%CI: 0.9670 - 0.9670) between the robot and human performed MICs. RASPs application to the five faecal samples highlighted the intra-animal diversity of gut commensal E. coli, identifying between five and nine unique isolate AMR phenotypes per sample. ConclusionsWhile adhering to internationally accepted guidelines, RASP was superior in throughput, cost and data resolution when compared to an experienced human technician. Integration of robotics platforms in the microbiology laboratory is a necessary advancement for future One-Health AMR endeavours.

microbiology↗