Biology subjects

Gibbons, H. S.

Publications and source records attributed to Gibbons, H. S..

4 recordsLinked to original sources

bioRxiv2021

Inhibition of select actinobacteria by the organophosphate pesticide chlorpyrifos

Organophosphorus compounds have an extensive history as both agricultural pesticides as well as chemical nerve agents. Decades of research have demonstrated numerous links between these chemicals and their direct and indirect effects on humans and other organisms. The inhibitory effects of organophosphate pesticides (OPPs) on metazoan physiology, are well-characterized; however, the effects of organophosphorus compounds on soil microbes - essential contributors to key agricultural processes - are poorly understood. Chlorpyrifos (CPF) is an OPP that is used globally for crop protection. Studies of CPF application to soils have shown transient effects on soil microbial communities with conflicting data. Here, we directly test the effect of CPF on a panel of 196 actinobacteria strains, examining the effects of CPF on their growth and in vitro phenotypes on solid media. Strains were grown and replica-plated onto media containing CPF or a vehicle control and grown at 28{degrees}C. CPF dramatically inhibited the growth of most strains and/or altered colony morphologies, with 13 strains completely inhibited by CPF. In disk diffusion assays with CPF, its degradation product 3,5,6-trichloropyridinol (TCP), malathion, parathion, monocrotophos and mevinphos, only CPF exhibited direct antimicrobial activity suggesting that the observed effects were due to CPF itself. IMPORTANCEChlorpyrifos is a globally used pesticide with documented neurological effects on non-target organisms in the environment. Finding that chlorpyrifos can inhibit the growth of some soil microbes in vitro may have implications for the composition, stability, and health of the soil microbiome. Due to the importance of soil microbes to numerous biogeochemical processes in agricultural systems, additional investigations into the non-target effects of CPF on soil microbes are clearly needed.

microbiology↗

bioRxiv2020

barCoder: a tool to generate unique, orthogonal genetic tags for qPCR detection

BackgroundTracking dispersal of microbial populations in the environment requires specific detection methods that discriminate between the target strain and all potential natural and artificial interferents, including previously utilized tester strains. Recent work has shown that genomic insertion of short identification tags, called "barcodes" here, allows detection of chromosomally tagged strains by real-time PCR. Manual design of these barcodes is feasible for small sets, but expansion of the technique to larger pools of distinct and well-functioning assays would be significantly aided by software-guided design. ResultsHere we introduce barCoder, a bioinformatics tool that facilitates the process of creating sets of uniquely identifiable barcoded strains. barCoder utilizes the genomic sequence of the target strain and a set of user-specified PCR parameters to generate a list of suggested barcode "modules" that consist of binding sites for primers and probes and appropriate spacer sequences. Each module is designed to yield optimal PCR amplification and unique identification. Optimal amplification includes metrics such as ideal Tm and G+C-content, appropriate spacing, and minimal stem-loop formation; unique identification includes low BLAST hits against the target organism, previously generated barcode modules, and databases, such as NCBI. We tested the ability of our algorithm to suggest appropriate barcodes by generating 12 modules for Bacillus thuringiensis serovar kurstaki, a simulant for the potential biowarfare agent Bacillus anthracis, and three each for other potential target organisms with variable G+C content. Real-time PCR detection assays directed at barcodes were specific and yielded minimal cross-reactivity with a panel of near-neighbor and potential contaminant materials. ConclusionsThe barCoder algorithm facilitates the generation of barcoded biological simulants by (a) eliminating the task of creating modules by hand, (b) minimizing optimization of PCR assays, and (c) reducing effort wasted on non-unique barcode modules.

bioinformatics↗

bioRxiv2018

The essential role of hypermutation in rapid adaptation to antibiotic stress

A common outcome of antibiotic exposure in patients and in vitro is the evolution of a hypermutator phenotype that enables rapid adaptation by pathogens. While hypermutation is a robust mechanism for rapid adaptation, it requires trade-offs between the adaptive mutations and the more common \"hitchhiker\" mutations that accumulate from the increased mutation rate. Using quantitative experimental evolution, we examined the role of hypermutation in driving adaptation of Pseudomonas aeruginosa to colistin. Metagenomic deep sequencing revealed 2,657 mutations at > 5% frequency in 1,197 genes and 761 mutations in 29 end point isolates. By combining genomic information, phylogenetic analyses, and statistical tests, we showed that evolutionary trajectories leading to resistance could be reliably discerned. In addition to known alleles such as pmrB, hypermutation allowed identification of additional adaptive alleles with epistatic relationships. Although hypermutation provided a short-term fitness benefit, it was detrimental to overall fitness. Alarmingly, a small fraction of the colistin adapted population remained colistin susceptible and escaped hypermutation. In a clinical population, such cells could play a role in re-establishing infection upon withdrawal of colistin. We present here a framework for evaluating the complex evolutionary trajectories of hypermutators that applies to both current and emerging pathogen populations.\n\nImportance\n\nBacteria can increase mutation rates in response to stress as an evolutionary strategy to avoid extinction. However, the complex mutational landscape of hypermutators makes it difficult to distinguish truly adaptive mutations from hitchhikers that follow similar evolutionary trajectories. We provide a framework for evaluating the complex evolutionary trajectories of hypermutators that can be applied to both current and emerging pathogen populations. Using Pseudomonas aeruginosa evolving to colistin as a model system, we examine the essential role of hypermutation in the evolution of resistance. Additionally, our results highlight the presence of a subset of cells that survive and remain susceptible during colistin exposure which can serve as a reservoir for re-infection upon withdrawal of the drug in clinical infections. This study provides a broad understanding of hypermutation during adaptation and describes a series of analyses that will be useful in identifying adaptive mutations in well annotated and novel bacterial mutator populations.

evolutionary biology↗

bioRxiv2018

Tracking a Serial Killer: Integrating Phylogenetic Relationships, Epidemiology, and Geography for Two Invasive Meningococcal Disease Outbreaks

BackgroundWhile overall rates of meningococcal disease have been declining in the United States for the past several decades, New York City (NYC) has experienced two serogroup C meningococcal disease outbreaks in 2005-2006 and in 2010-2013. The outbreaks were centered within drug use and sexual networks, were difficult to control, and required vaccine campaigns.\n\nMethodsWhole Genome Sequencing (WGS) was used to analyze preserved meningococcal isolates collected before and during the two outbreaks. We integrated and analyzed epidemiologic, geographic, and genomic data to better understand transmission networks among patients. Betweenness centrality was used as a metric to understand the most important geographic nodes in the transmission networks. Comparative genomics was used to identify genes associated with the outbreaks.\n\nResultsNeisseria meningitidis serogroup C (ST11/ET-37) was responsible for both outbreaks with each outbreak having distinct phylogenetic clusters. WGS did identify some misclassifications of isolates that were more distant from the rest of the outbreak, as well as those that should have been included based on high genomic similarity. Genomes for the second outbreak were more similar than the first and no mutation was found to either be unique or specific to either outbreak lineage. Betweenness centrality as applied to transmission networks based on phylogenetic analysis demonstrated that the outbreaks were transmitted within focal communities in NYC with few transmission events to other locations.\n\nConclusionsNeisseria meningitidis is an ever changing pathogen and comparative genomic analyses can help elucidate how it spreads geographically to facilitate targeted interventions to interrupt transmission.

genomics↗