Biology subjects

Arnold, B. J.

Publications and source records attributed to Arnold, B. J..

10 recordsLinked to original sources

bioRxiv2024

Quantifying higher-order epistasis: beware the chimera

Epistasis, or interactions in which alleles at one locus modify the fitness effects of alleles at other loci, plays a fundamental role in genetics, protein evolution, and many other areas of biology. Epistasis is typically quantified by computing the deviation from the expected fitness under an additive or multiplicative model using one of several formulae. However, these formulae are not all equivalent. Importantly, one widely used formula - which we call the chimeric formula - measures deviations from a multiplicative fitness model on an additive scale, thus mixing two measurement scales. We show that for pairwise interactions, the chimeric formula yields a different magnitude, but the same sign (synergistic vs. antagonistic) of epistasis compared to the multiplicative formula that measures both fitness and deviations on a multiplicative scale. However, for higher-order interactions, we show that the chimeric formula can have both different magnitude and sign compared to the multiplicative formula -- thus confusing negative epistatic interactions with positive interactions, and vice versa. We resolve these inconsistencies by deriving fundamental connections between the different epistasis formulae and the parameters of the multivariate Bernoulli distribution. Our results demonstrate that the additive and multiplicative epistasis formulae are more mathematically sound than the chimeric formula. Moreover, we demonstrate that the mathematical issues with the chimeric epistasis formula lead to markedly different biological interpretations of real data. Analyzing multi-gene knockout data in yeast, multi-way drug interactions in E. coli, and deep mutational scanning (DMS) of several proteins, we find that 10 - 60% of higher-order interactions have a change in sign with the multiplicative or additive epistasis formula. These sign changes result in qualitatively different findings on functional divergence in the yeast genome, synergistic vs. antagonistic drug interactions, and and epistasis between protein mutations. In particular, in the yeast data, the more appropriate multiplicative formula identifies nearly 500 additional negative three-way interactions, thus extending the trigenic interaction network by 25%.

genetics↗

bioRxiv2023

Mapping the topography of spatial gene expression with interpretable deep learning

Spatially resolved transcriptomics technologies provide high-throughput measurements of gene expression in a tissue slice, but the sparsity of this data complicates the analysis of spatial gene expression patterns such as gene expression gradients. We address these issues by deriving a topographic map of a tissue slice--analogous to a map of elevation in a landscape--using a novel quantity called the isodepth. Contours of constant isodepth enclose spatial domains with distinct cell type composition, while gradients of the isodepth indicate spatial directions of maximum change in gene expression. We develop GASTON, an unsupervised and interpretable deep learning algorithm that simultaneously learns the isodepth, spatial gene expression gradients, and piecewise linear functions of the isodepth that model both continuous gradients and discontinuous spatial variation in the expression of individual genes. We validate GASTON by showing that it accurately identifies spatial domains and marker genes across several biological systems. In SRT data from the brain, GASTON reveals gradients of neuronal differentiation and firing, and in SRT data from a tumor sample, GASTON infers gradients of metabolic activity and epithelial-mesenchymal transition (EMT)-related gene expression in the tumor microenvironment.

bioinformatics↗

bioRxiv2023

HATCHet2: clone- and haplotype-specific copy number inference from bulk tumor sequencing data

Multi-region DNA sequencing of primary tumors and metastases from individual patients helps identify somatic aberrations driving cancer development. However, most methods to infer copy-number aberrations (CNAs) analyze individual samples. We introduce HATCHet2 to identify haplotype- and clone-specific CNAs simultaneously from multiple bulk samples. HATCHet2 introduces a novel statistic, the mirrored haplotype B-allele frequency (mhBAF), to identify mirrored-subclonal CNAs having different numbers of copies of parental haplotypes in different tumor clones. HATCHet2 also has high accuracy in identifying focal CNAs and extends the earlier HATCHet method in several directions. We demonstrate HATCHet2s improved accuracy using simulations and a single-cell sequencing dataset. HATCHet2 analysis of 50 prostate cancer samples from 10 patients reveals previously-unreported mirrored-subclonal CNAs affecting cancer genes.

cancer biology↗

bioRxiv2022

Greater resistance to footshock punishment in female C57BL/6J mice responding for ethanol

BackgroundOne characteristic of alcohol use disorder (AUD) is compulsive drinking, or drinking despite negative consequences. When quinine is used to model such aversion-resistant drinking, female rodents typically are more resistant to punishment than males. Using an operant response task where C57BL/6J responded for ethanol (EtOH) mixed with quinine, we previously demonstrated that female mice tolerate higher concentrations of quinine in EtOH than males. Here, we aimed to determine if this female vulnerability to aversion-resistant drinking behavior is similarly observed when footshock punishment is used. MethodsMale and female C57BL/6J mice were trained to respond for 10% EtOH in an operant task on a fixed ratio 3 schedule. After consistent responding, mice were tested in a punishment session using either a 0.25 mA or 0.35 mA footshock. To assess footshock sensitivity, a subset of mice underwent a flinch, jump, vocalize test in which behavioral responses to increasing amplitudes of footshock (0.05 - 0.95 mA) were assessed. In a separate cohort of mice, males and females were trained to respond for 2.5% sucrose and responses were punished using a 0.25 mA footshock. ResultsMales and females continued to respond for 10% EtOH when paired with a 0.25 mA footshock. Females alone continued to respond for EtOH when a 0.35 mA footshock was delivered. Both males and females reduced responding for 2.5% sucrose when punished with a 0.25 mA footshock. Finally, footshock sensitivity in the flinch, jump, vocalize test did not differ by sex. ConclusionsFemales continue to respond for 10% EtOH despite a 0.35 mA footshock and this behavior is not due to differences in footshock sensitivity between males and females. These results suggest that female C57BL/6J mice are generally more resistant to punishment in an operant self-administration paradigm. These results add to the literature characterizing aversion-resistant alcohol drinking behaviors in females.

neuroscience↗

bioRxiv2019

Fine-scale haplotype structure reveals strong signatures of positive selection in a recombining bacterial pathogen

Identifying the forces that create and shape ecologically meaningful variation in bacteria remains an important challenge. For recombining bacteria, the sign and strength of linkage provide a unique lens into ongoing selection. We show derived alleles less than 300bp apart in Neisseria gonorrhoeae exhibit more coupling linkage than repulsion linkage, a pattern that cannot be explained by limited recombination or neutrality as these couplings are significantly stronger for nonsynonymous alleles compared to synonymous alleles. While linkage is shaped by many evolutionary processes, extensive simulations show only two distinct forms of positive selection can drive an excess of coupling linkage between neighboring nonsynonymous alleles: directional selection on introgressed alleles or selection that maintains distinct haplotypes in the presence of recombination. Our results establish a framework for identifying patterns of selection in fine-scale haplotype structure that indicate specific ecological processes in species that recombine with distantly related lineages or possess coexisting adaptive haplotypes.

evolutionary biology↗

bioRxiv2018

Prediction of post-vaccine population structure of Streptococcus pneumoniae using accessory gene frequencies

Predicting how pathogen populations will change over time is challenging. Such has been the case with Streptococcus pneumoniae, an important human pathogen, and the pneumococcal conjugate vaccines (PCVs), which target only a fraction of the strains in the population. Here, we use the frequencies of accessory genes to predict changes in the pneumococcal population after vaccination, hypothesizing that these frequencies reflect negative frequency-dependent selection (NFDS) on the gene products. We find that the standardized predicted fitness of a strain estimated by an NFDS-based model at the time the vaccine is introduced enables to predict whether the strain increases or decreases in prevalence following vaccination. Further, we are able to forecast the equilibrium post-vaccine population composition and assess the invasion capacity of emerging lineages. Overall, we provide a method for predicting the impact of an intervention on pneumococcal populations with potential application to other bacterial pathogens in which NFDS is a driving force.

evolutionary biology↗

bioRxiv2018

An introduced crop plant is driving diversification of the virulent bacterial pathogen Erwinia tracheiphila

Erwinia tracheiphila is the causal agent of bacterial wilt of cucurbits, an economically important phytopathogen affecting few cultivated Cucurbitaceae host plant species in temperate Eastern North America. However, essentially nothing is known about E. tracheiphila population structure or genetic diversity. To address this shortcoming, a representative collection of 88 E. tracheiphila isolates was gathered from throughout its geographic range, and their genomes were sequenced. Phylogenomic analysis revealed three genetic clusters with distinct hrpT3SS virulence gene repertoires, host plant association patterns, and geographic distributions. The low genetic variation within each cluster suggests a recent population bottleneck followed by population expansion. We showed that in the field and greenhouse, cucumber (Cucumis sativus), which was introduced to North America by early Spanish conquistadors, is the most susceptible host plant species, and the only species susceptible to isolates from all three lineages. The establishment of large agricultural populations of highly susceptible C. sativus in temperate Eastern North America may have facilitated the original emergence of E. tracheiphila into cucurbit agro-ecosystems, and this introduced plant species may now be acting as a highly susceptible reservoir host. Our findings have broad implications for agricultural sustainability by drawing attention to how worldwide crop plant movement, agricultural intensification and locally unique environments may affect the emergence, evolution, and epidemic persistence of virulent microbial pathogens.\n\nImportanceErwinia tracheiphila is a virulent phytopathogen that infects two genera of cucurbit crop plants, Cucurbita spp. (pumpkin and squash) and Cucumis spp. (muskmelon and cucumber). One of the unusual ecological traits of this pathogen is that it is limited to temperate Eastern North America. Here, we complete the first large-scale sequencing of an E. tracheiphila isolate collection. From phylogenomic, comparative genomic, and empirical analyses, we find that introduced Cucumis spp. crop plants are driving the diversification of E. tracheiphila into multiple, closely related lineages. Together, the results from this study show that locally unique biotic (plant population) and abiotic (climate) conditions can drive the evolutionary trajectories of locally endemic pathogens in unexpected ways.

evolutionary biology↗

bioRxiv2018

Azithromycin resistance through interspecific acquisition of an epistasis dependent efflux pump component and transcriptional regulator in Neisseria gonorrhoeae

Mosaic interspecifically acquired alleles of the multiple transferable resistance (mtr) efflux pump operon correlate with reduced susceptibility to azithromycin in Neisseria gonorrhoeae in epidemiological studies. However, whether and how these alleles cause resistance is unclear. Here, we use population genomics, transformations, and transcriptional analyses to dissect the relationship between variant mtr alleles and azithromycin resistance. We find that the locus encompassing the mtrR transcriptional repressor and the mtrCDE pump is a hotspot of interspecific recombination introducing alleles from N. meningitidis and N. lactamica into N. gonorrhoeae, with multiple rare haplotypes in linkage disequilibrium at mtrD and the mtr promoter region. Transformations demonstrated that resistance is mediated through epistasis between these two loci and that the full length of the mosaic mtrD allele is required. Gene expression profiling revealed the mechanism of resistance in mosaics couples the novel mtrDalleles with promoter mutations enhancing expression of the pump. Overall, our results demonstrate that epistatic interactions at mtr gained from multiple Neisseria has contributed to azithromycin resistance in the gonococcal population.\n\nAUTHOR SUMMARYNeisseria gonorrhoeae is the sexually transmitted bacterial pathogen responsible for over 100 million cases of gonorrhea worldwide each year. The incidence of reduced susceptibility to the macrolide class antibiotic azithromycin has increased in the past decade; however, a large proportion of the genetic basis of resistance to this drug remains unexplained. Recently, resistance has been shown to be highly associated with mosaic alleles of the multiple transferable resistance (mtr) efflux pump, which have been gained via horizontal gene exchange with other Neisseria. However, if and how these alleles caused resistance was unknown. Here, we demonstrate that resistance has been gained through epistasis between mtrD and the mtr promoter region using evidence from both population genomics and experimental genetic manipulation. Epistasis also acts within the mtrD locus alone, requiring the full length of the gene for phenotypic resistance. Transcriptomic profiling indicates that the mechanism of resistance in mosaics is likely derived from both structural changes to mtrD, coupled with promoter mutations that result in regulatory changes to mtrCDE.

microbiology↗

bioRxiv2017

Weak epistasis may drive adaptation in recombining bacteria

The impact of epistasis on the evolution of multilocus traits depends on recombination. Population genetic theory has been largely developed for eukaryotes, many of which recombine so frequently that epistasis between polymorphisms has not been considered to play a large role in adaptation and has been compared to the fleeting influence of non-heritable effects. Many bacteria also recombine, some to the degree that their populations are described as panmictic or freely recombining. However, whether this recombination is sufficient to limit the ability of selection to act on epistatic contributions to fitness is unknown. We create a sensitive method to quantify homologous recombination in five bacterial pathogens and use these parameter estimates in a multilocus model of bacterial evolution with additive and epistatic effects. We find that even for highly recombining species (e.g. Streptococcus pneumoniae or Helicobacter pylori), selection may act on the cumulative effects of weak (as well as strong) interactions between distant mutations since homologous recombination typically transfers only short segments. Furthermore, whether selection acts more efficiently on physically proximal loci depends on the average recombination tract length. Epistasis may thus play an important role in the adaptive evolution of bacteria and, unlike in eukaryotes, does not need to be strong, involve near loci, or require specific metapopulation dynamics.

evolutionary biology↗

bioRxiv2017

Longitudinal samples of bacterial genomes potentially bias evolutionary analyses

Samples of bacteria collected over a period of time are attractive for several reasons, including the ability to estimate the molecular clock rate and to detect fluctuations in allele frequencies over time. However, longitudinal datasets are occasionally used in analyses that assume samples were collected contemporaneously. Using both simulations and genomic data from Neisseria gonorrhoeae, Streptococcus mutans, Campylobacter jejuni, and Helicobacter pylori, we show that longitudinal samples (spanning more than a decade in real data) may suffer from considerable bias that inflates estimates of recombination and the number of rare mutations in a sample of genomic sequences. While longitudinal data are frequently accounted for using the serial coalescent, many studies use other programs or metrics, such as Tajimas D, that are sensitive to these sampling biases and contain genomic data collected across many years. Notably, longitudinal samples from a population of constant size may exhibit evidence of exponential growth. We suggest that population genomic studies of bacteria should routinely account for temporal diversity in samples or provide evidence that longitudinal sampling bias does not affect conclusions.

genomics↗