Biology subjects

Hsu, B.

Publications and source records attributed to Hsu, B..

4 recordsLinked to original sources

bioRxiv2023

Harnessing the power of regional baselines for broad-scale genetic stock identification: A multistage, integrated, and cost-effective approach

Genetic stock identification (GSI) estimates the contribution of each population to a mixture and these analyses are usually conducted regionally using genetic baselines specific to the stocks expected in that region. Often these regional baselines cannot be combined to produce broader geographical baselines. In cases where the mixture contains stocks spanning across a wide area a broad-scale baseline is created, but these baselines often are unable to resolve among regional stocks. Here, we introduce a new GSI method to harness the resolution capabilities of baselines developed for regional applications in the analyses of mixtures containing fish from a broad geographic range. This multistage process allows for disparate baselines to be used in a single integrated process that estimates the propagated errors from each stage. The baselines used by this model do not require any overlap in markers or in populations representing the broad-scale or regional baselines. The integrated multistage framework allows GSI of a wide geographic area without first developing a large scale, high resolution genetic baseline, or dividing a mixture sample into smaller regions beforehand. This approach is more cost-effective than updating range-wide baselines with all critical regionally important markers.

genetics↗

bioRxiv2019

Stable neutralization of virulent bacteria using temperate phage in the mammalian gut

Elimination or alteration of select members of the gut microbiota is key to therapeutic efficacy. However, the complexity of these microbial inhabitants makes it challenging to precisely target bacteria without unexpected cascading effects. Here, we use bacteriophage to deliver exogenous genes to specific bacteria by genomic integration of temperate phage for long-lasting modification. As a real-world therapeutic test, we engineered {lambda} phage to transcriptionally-repress shigatoxin by using genetic hybrids between {lambda} and other lambdoid phages to overcome resistance encoded by the virulent prophage derived from enterohemorrhagic E. coli. We show that a single dose of engineered phage propagates throughout the bacterial community and reduces shigatoxin production in an enteric mouse model of infection without markedly affecting bacterial concentrations. We thus minimize the selection for resistance by relying on anti-virulence and not anti-bacterial action. Our work reveals a new framework for transferring functions to bacteria within their native environment.

synthetic biology↗

bioRxiv2019

Auto-regressive modeling and diagnostics for qPCR amplification

Current methods used to analyze real-time quantitative polymerase chain reaction (qPCR) data exhibit systematic deviations from the assumed model over the progression of the reaction. Slight variations in the amount of the initial target molecule or in early amplifications are likely responsible for these deviations. Commonly-used 4- and 5-parameter sigmoidal models appear to be particularly susceptible to this issue, often displaying patterns of autocorrelation in the residuals. The presence of this phenomenon, even for technical replicates, suggests that these parametric models may be misspecified. Specifically, they do not account for the sequential dependent nature of qPCR fluorescence measurements. We demonstrate that a Smooth Transition Autoregressive (STAR) model addresses this limitation by explicitly modeling the dependence between cycles and the gradual transition between amplification regimes. In summary, application of a STAR model to qPCR amplification data improves model fit and reduces autocorrelation in the residuals.

bioinformatics↗

bioRxiv2019

De novo emergence of adaptive membrane proteins from thymine-rich intergenic sequences

Recent evidence demonstrates that novel protein-coding genes can arise de novo from intergenic loci. This evolutionary innovation is thought to be facilitated by the pervasive translation of intergenic transcripts, which exposes a reservoir of variable polypeptides to natural selection. Do intergenic translation events yield polypeptides with useful biochemical capacities? The answer to this question remains controversial. Here, we systematically characterized how de novo emerging coding sequences impact fitness. In budding yeast, overexpression of these sequences was enriched in beneficial effects, while their disruption was generally inconsequential. We found that beneficial emerging sequences have a strong tendency to encode putative transmembrane proteins, which appears to stem from a cryptic propensity for transmembrane signals throughout thymine-rich intergenic regions of the genome. These findings suggest that novel genes with useful biochemical capacities, such as transmembrane domains, tend to evolve de novo within intergenic loci that already harbored a blueprint for these capacities.

evolutionary biology↗