Biology subjects

Hamilton, R.

Publications and source records attributed to Hamilton, R..

16 recordsLinked to original sources

bioRxiv2026

Genomic indicators of risk and resilience in global leatherback turtle populations

Understanding the drivers of genomic health and their consequences for population viability is often overlooked but potentially important to effective conservation amidst the biodiversity crisis of the Anthropocene. Leatherback turtle (Dermochelys coriacea) populations have declined globally due to anthropogenic factors, with some populations losing over 90% of their abundance over the past 30-50 years. While conservation efforts have been successful in stabilizing some populations, others continue to decline, and the reasons for these differential trajectories remain unclear. To assess how recent demographic factors, such as population size and decline, influence population genomic health, we combined population monitoring information with medium depth whole-genome and reduced representation resequencing data from globally representative populations. We found that small-stable populations have lower genomic diversity and higher inbreeding than large declining populations, reflecting prolonged small population sizes and limited gene flow. Yet, small-stable populations also show evidence of deleterious allele purging, suggesting genetic resilience. This, combined with lack of detectable genomic erosion over the study period, provides hope for potential recovery of healthy leatherback populations provided that anthropogenic threats are effectively mitigated. However, potential time lags and possible recent increases in inbreeding among close relatives in recently declined populations warrant continued monitoring and assessment. Genomic and abundance-based metrics were less aligned following rapid population declines, emphasizing the different timescales of the evolutionary and demographic processes they reflect, respectively, and the strength in their complementary, integrative use for extinction risk assessments. This also supports that it is not too late to turn the tide for recently declined leatherback populations and that continued investment in conservation efforts and threat reductions are warranted. Collectively, our results highlight how recent and historical demography shapes current genomic health and recovery potential in leatherback turtles, aids understanding of current risks and informs future conservation and management strategies.

ecology↗

bioRxiv2026

Control of grain dimensions via ALLENE OXIDE CYCLASE

Cereal grain is a global food staple. Grain formation starts with fertilization of the embryo sac which generates filial tissues, such as the embryo and endosperm, that grow embedded in the maternal ovule and surrounding ovary wall. Maternal tissues provide nutrition and protection but are progressively reduced and degraded, such that filial tissues dominate the mature grain. While we know some enzymatic players, regulation of this process in temperate cereals like wheat and barley, remains less understood. However, previous work suggested a role for the phytohormone Jasmonate (JA). To learn more, we edited the barley ALLENE OXIDASE CYCLASE (HvAOC) gene encoding a JA biosynthetic enzyme. Defective HvAOC alleles caused enhanced vegetative growth, faster flowering and larger, heavier grain - phenotypes rescued by MeJA treatment. HvAOC control of final grain parameters is parentally-derived, consistent with enriched HvAOC expression in maternal compared to filial tissues. Defective HvAOC function enlarged maternal tissues involved in nutrient transfer, correlating with larger endosperm and higher expression of genes linked to sucrose transport. This work provides the first genetic dissection of JA in barley and highlights a key role for HvAOC in the coordination between growth and death of maternal tissues with grain size and weight.

plant biology↗

bioRxiv2025

Coevolutionary constraints of Zika virus nonstructural protein 5 replication and interferon antagonism activities

The flavivirus nonstructural protein 5 performs multiple functions during infection, including RNA replication and type I interferon signaling antagonism. Although flavivirus NS5 proteins inhibit IFN signaling through distinct mechanisms, which suggests evolutionary flexibility, the evolutionary constraints for these activities to coexist within a single protein remain to be determined. Here, we mapped the Zika virus NS5 STAT2 antagonism determinants and compared them with replication constraints defined by deep mutational scanning. Antagonism and replication determinant extensively overlapped, and no single amino acid substitution eliminated antagonism without impairing replication. Resolving these fitness landscapes in parallel identified specific combinations of partially functional substitutions that retained replication capacity while markedly reducing antagonism. These viruses were profoundly attenuated in human STAT2 knock-in mice. Our results uncover a fundamental evolutionary constraint linking replication and immune evasion activities in NS5, highlight that STAT2 antagonism is essential for ZIKV pathogenesis and provide new avenues for attenuated ZIKV vaccines.

microbiology↗

bioRxiv2025

Frontoamygdala hyperconnectivity predicts autonomic dysregulation and persisting symptoms in sports-related concussion

OBJECTIVEWe investigated longitudinal trajectories of resting-state fMRI (rsfMRI), autonomic function, and symptoms after sport-related concussion (SRC). BACKGROUNDLimbic circuitry may be particularly vulnerable to traumatic brain injury (TBI), which could explain the affective and autonomic dysfunction some patients develop. Relatively few studies have performed longitudinal rsfMRI analyses in concussion and fewer have combined imaging with autonomic and symptom data. We leveraged published limbic rsfMRI networks centered on the amygdala that include central autonomic structures in frontal and temporal lobes and their visceromotor targets. We hypothesized that frontoamygdala connectivity would differentiate athletes with SRC from matched, in-sport controls (ISC), predict autonomic function, and predict symptom recovery. DESIGN/METHODSUsing independent-samples t-tests, we compared rsfMRI connectivity strength in amygdala networks in college athletes with SRC (SRC: n=31, female=14) at three time points after concussion (T1[≤]4 days, T2=10-14 days, T3=60-90 days) and healthy, matched controls without a concussion in the same sport (ISC: n=36, female=17). RESULTSSRC athletes showed significantly greater frontoamygdala connectivity compared to ISCs at the acute and subacute post-injury time points (T1 p=0.003, T2 p=0.014) that normalized to control-level connectivity by the chronic time point (T3 p=0.182). When testing whether autonomic function interacts with network connectivity trajectory, we found that opposing trajectories of frontoamygdala connectivity between SRC athletes with higher versus lower acute heart rate variability (HRV), as measured by pNN50 (percentage of intervals between successive normal sinus beats greater than 50ms). SRC athletes with higher HRV acutely post-injury had significantly greater acute frontoamygdala connectivity compared to ISCs at T1; connectivity in these high-HRV SRC athletes normalized to control level over time (T1 p=0.001, T2 p=0.055, T3 p=0.576). SRC athletes with lower HRV acutely post-injury had control-level frontoamygdala connectivity at T1; connectivity in these low-HRV SRC athletes significantly exceeded control-level connectivity at T3 (T1 p=0.429, T2 p=0.050, T3 p=0.002). Furthermore, those SRC athletes with the greatest frontoamygdala connectivity at T3, had the most persistent symptoms on the graded symptom checklist at T3 (r=0.635, p=0.001). Differences in diffusion-tensor-imaging-based measures of structural connectivity in the uncinate fasciculus, the fiber bundle most critical to our frontoamygdala network, could not account for these relationships. CONCLUSIONSThese results suggest that increased connectivity in amygdala circuitry acutely after a concussion and its normalization over time may be protective or compensatory; acute measures of amygdala network connectivity and measures of HRV may be valuable biomarkers for predicting symptom persistence.

neuroscience↗

bioRxiv2024

Whole-Genome Sequencing of the Wild Barley Diversity Collection: A Resource for Identifying and Exploiting Genetic Variation for Cultivated Barley Improvement

To exploit allelic variation in Hordeum vulgare subsp. spontaneum, the Wild Barley Diversity Collection was evaluated for several agronomic traits and subjected to paired-end Illumina sequencing at [~]9X depth, generating 109.5 million single nucleotide polymorphisms after alignment to the Morex V3 assembly. A genome-wide association study of lemma color identified one marker-trait association (MTA) on chromosome 1HL close to HvBlp, the cloned gene controlling black lemma. Four MTAs were identified for stem rust resistance: one co-locating to the complex RMRL1-RMRL2 locus on 5HL, and three novel loci on 1HS, 1HL, and 5HL. Six MTAs for days to heading (DTH) on vernalized plants were identified on all chromosomes except 1H and 6H. Two MTAs for DTH on non-vernalized plants were identified on chromosomes 1HL and 2HS. All MTAs for DTH were novel. The whole genome sequence data described herein will facilitate the identification and utilization of new alleles for barley improvement.

genomics↗

bioRxiv2024

Modification and Analysis of Context-Specific Genome-Scale Metabolic Models: Methane-Utilizing Microbial Chassis as a Case Study

Context-specific genome-scale model (CS-GSM) reconstruction is becoming an efficient strategy for integrating and cross-comparing experimental multi-scale data to explore the relationship between cellular genotypes, facilitating fundamental or applied research discoveries. However, the application of CS modeling for non-conventional microbes is still challenging. Here, we present a GUI interface that integrates COBRApy, EscherPy, and RIPTiDe Python-based tools within the BioUML platform and streamlines the reconstruction and interrogation of the CS genome-scale metabolic frameworks via Jupyter Notebook. The approach was tested using -omics data collected for Methylotuvimicrobium alcaliphilum 20ZR, a prominent microbial chassis for methane capturing and valorization. We optimized the previously reconstructed whole genome-scale metabolic network by adjusting the flux distribution using gene expression data. The outputs of the automatically reconstructed CS metabolic network were comparable to manually optimized iIA409 models for Ca-growth conditions. However, the CS model questions the reversibility of the phosphoketolase pathway and suggested higher flux via primary oxidation pathways. The model also highlighted unresolved carbon partitioning between assimilatory and catabolic pathways at the formaldehyde-formate node. Only a very few genes and only one enzyme with a predicted function in C1-metabolism, a homolog of the formaldehyde oxidation enzyme (fae1-2), showed a significant change in expression in La-growth conditions. The CS-GSM predictions agreed with the experimental measurements under the assumption that the Fae1-2 is a part of tetrahydrofolate-linked pathway. The cellular roles of the tungsten (W)-dependent formate dehydrogenase (fdhAB) and fae-homologues (fae1-2, and fae3) were investigated via mutagenesis. The phenotype of the fdhAB mutant followed the model prediction. Furthermore, more significant reduction of the biomass yield was observed during growth in La-supplemented media, confirming a higher flux through formate. M. alcaliphilum 20ZR mutants lacking fae1-2 did not display any significant defects in methane or methanol-dependent growth. However, contrary to fae, the fae1-2 homolog failed to restore the formaldehyde activating enzyme function in complementation tests. Overall, the presented data suggest that the developed computational workflow supports the reconstruction and validation of CS-GSM networks of non-model microbes.

systems biology↗

bioRxiv2024

Microbial Hauberks: Composition and Function of Surface Layer Proteins in Gammaproteobacterial Methanotrophs

Many species of proteobacterial methane-consuming bacteria (methanotrophs) form a hauberk-like envelope represented by a surface (S-) layer protein matrix. While several proteins were predicted to be associated with the cell surface, the composition and function of the hauberk matrix remained elusive. Here we report the identification of the genes encoding the hauberk-forming protein in two gamma-proteobacterial (Type I) methanotrophs, Methylotuvimicrobium buryatense 5GB1 (EQU24_15540) and Methylotuvimicrobium alcaliphilum 20ZR (MEALZ_0971 and MEALZ_0972). The proteins share 40% AA identity with each other and are distantly related to the RsaA proteins from Caulobacter crescentus (20% AA identity). Deletion of these genes resulted in loss of the characteristic hauberk pattern on the cell surface. A set of transcriptional fusions between the MEALZ_0971 and a superfolder green fluorescent protein (sfGFP) further confirmed its surface localization. The functional roles of the hauberk and cell-surface associated proteins, including MEALZ_0971, MEALZ_0972, EQU24_15540, and a copper-induced CorA protein, were further investigated via gene expression studies and phenotypic tests. The hauberk core protein shows constitutive expression across 18 growth conditions. The M. alcaliphilum 20ZR{Delta}0971 showed reduced growth at high salinity, high methanol and metal-limited conditions, suggesting a role in cell-envelope stability and metal scavenging. Overall, understanding the genetics, composition and cellular functions of the S-layers contributes to our knowledge of methanotroph adaptation to environmental perturbations and opens a promising prospect for (nano)biotechnology applications.

microbiology↗

bioRxiv2023

Accurate quantification of lysyl oxidase concentration in human tissue

The family of Lysyl oxidase enzymes play fundamental roles in the formation of the extracellular matrix, through catalyzing the crosslinking of collagen and elastin fibers. Lysyl oxidase (LOX) -- one of the 5 family members (LOX, LOXL1-4), is a disease biomarker, with blood concentration positively correlating with progression of fibrosis or cancer. An accurate quantification of LOX concentration can support diagnosis, monitoring of disease progression or treatment success. However, reported LOX concentrations in human blood are inconsistent. Therefore, a novel, high-throughput and sensitive digital enzyme-linked immunosorbent assay was developed using two validated and selective human anti-LOX antibodies and single molecule array technology. Both, the 56 kDa pro-form and the 32 kDa active form can be accurately measured from recombinant and native protein. The serum LOX concentration correlated with LOX activity measured in the same platform using a bio-probe. The usefulness of this technology was demonstrated in serum from bladder cancer patients wherein LOX concentration was significantly higher compared to the healthy subjects. This study demonstrates the validation and use of a sensitive and accurate method for measuring LOX concentration in human samples. This novel method may be superior than some commercially available enzyme-linked immunosorbent assay kits for accurate measurement of LOX concentrations in clinical settings.

molecular biology↗

bioRxiv2023

Systematically testing human HMBS missense variants to reveal mechanism and pathogenic variation

Defects in hydroxymethylbilane synthase (HMBS) can cause Acute Intermittent Porphyria (AIP), an acute neurological disease. Although sequencing-based diagnosis can be definitive, ~[1/3] of clinical HMBS variants are missense variants, and most clinically-reported HMBS missense variants are designated as "variants of uncertain significance" (VUS). Using saturation mutagenesis, en masse selection, and sequencing, we applied a multiplexed validated assay to both the erythroid-specific and ubiquitous isoforms of HMBS, obtaining confident functional impact scores for >84% of all possible amino-acid substitutions. The resulting variant effect maps generally agreed with biochemical expectation. However, the maps showed variants at the dimerization interface to be unexpectedly well tolerated, and suggested residue roles in active site dynamics that were supported by molecular dynamics simulations. Most importantly, these HMBS variant effect maps can help discriminate pathogenic from benign variants, proactively providing evidence even for yet-to-be-observed clinical missense variants.

molecular biology↗

bioRxiv2022

Individual-level Functional ConnectivityPredicts Cognitive Control Efficiency

Cognitive control (CC) is a vital component of cognition associated with problem-solving in everyday life. Many neurological and neuropsychiatric conditions have deficits associated with CC. CC is composed of multiple behaviors including switching, inhibiting, and updating. The fronto-parietal control network B (FPCN-B), the dorsal attention network (DAN), the cingulo-opercular network (CON) and the dorsal default-mode network (dorsal-DMN) have been associated with switching and inhibiting behaviors. However, our understanding of how these brain regions interact to bring about CC behaviors is still unclear. In the current study, participants performed two in-scanner tasks that required switching and inhibiting. We then used a series of support vector regression (SVR) models containing individually-estimated functional connectivity between the networks of interest derived during tasks and at rest to predict inhibition and switching behaviors in individual subjects. We observed that the combination of between-network connectivity from these individually estimated functional networks predicted accurate and timely inhibition and switching behaviors in individuals. We also observed that the relationships between canonical task-positive and task-negative networks predicted inhibiting and switching behaviors. Finally, we observed a functional dissociation between the FPCN-A and FPCNB during rest, and task performance predicted inhibiting and switching behaviors. These results suggest that individually estimated networks can predict individual CC behaviors, that between-network functional connectivity estimated within individuals is vital to understanding how CC arises, and that the fractionation of the FPCN and the DMN may be associated with different behaviors than their canonically accepted behaviors.

neuroscience↗

bioRxiv2020

Combining genome-wide studies of breast, prostate, ovarian and endometrial cancers maps cross-cancer susceptibility loci and identifies new genetic associations

We report a meta-analysis of breast, prostate, ovarian, and endometrial cancer genome-wide association data (effective sample size: 237,483 cases/317,006 controls). This identified 465 independent lead variants (P<5x10-8) across 192 genomic regions. Four lead variants were >1Mb from previously identified risk loci for the four cancers and an additional 23 lead variant-cancer associations were novel for one of the cancers. Bayesian models supported pleiotropic effects involving at least two cancers at 222/465 lead variants in 118/192 regions. Gene-level association analysis identified 13 shared susceptibility genes (P<2.6x10-6) in 13 regions not previously implicated in any of the four cancers and not uncovered by our variant-level meta-analysis. Several lead variants had opposite effects across cancers, including a cluster of such variants in the TP53 pathway. Fifty-four lead variants were associated with blood cell traits and suggested genetic overlaps with clonal hematopoiesis. Our study highlights the remarkable pervasiveness of pleiotropy across hormone-related cancers, further illuminating their shared genetic and mechanistic origins at variant- and gene-level resolution.

genetics↗

bioRxiv2018

The Signaling Pathways Project: an integrated ‘omics knowledgebase for mammalian cellular signaling pathways

Integrated mining of public transcriptomic and ChIP-Seq datasets has the potential to illuminate facets of mammalian cellular signaling pathways not yet explored in the research literature. Here, we designed a web knowledgebase, the Signaling Pathways Project (SPP), which incorporates stable community classifications of the four major categories of signaling pathway node (receptors, enzymes, transcription factors and co-nodes) and their cognate bioactive small molecules (BSMs). We then mapped over 10,000 public transcriptomic or cistromic experiments to their relevant signaling pathway node, BSM or biosample of study. To provide for prediction of pathway node-target transcriptional regulatory relationships, we generated consensus omics signatures, or consensomes, based on measures of significant differential expression of genomic targets across all underlying transcriptomic experiments. To expose the SPP knowledgebase to researchers, a web browser interface accommodates a variety of routine data mining strategies. Consensomes were validated using alignment with literature-based knowledge, gene target-level integration of transcriptomic and ChIP-Seq data points, and in bench experiments that confirmed previously uncharacterized node-gene target regulatory relationships. SPP is freely accessible at https://beta.signalingpathways.org.

bioinformatics↗

bioRxiv2018

Algorithm for Reliable Detection of Beat Onsets in Cerebral Blood Flow Velocity Signals

Transcranial Doppler (TCD) ultrasound has been demonstrated to be a valuable tool for assessing cerebral hemodynamics via measurement of cerebral blood flow velocity (CBFV), with a number of established clinical indications. However, CBFV waveform analysis depends on reliable pulse onset detection, an inherently difficult task for CBFV signals acquired via TCD. We study the application of a new algorithm for CBFV pulse segmentation, which locates pulse onsets in a sequential manner using a moving difference filter and adaptive thresholding. The test data set used in this study consists of 92,012 annotated CBFV pulses, whose quality is representative of real world data. On this test set, the algorithm achieves a true positive rate of 99.998% (2 false negatives), positive predictive value of 99.998% (2 false positives), and mean temporal offset error of 6.10 {+/-} 4.75 ms. We do note that in this context, the way in which true positives, false positives, and false negatives are defined caries some nuance, so care should be taken when drawing comparisons to other algorithms. Additionally, we find that 97.8% and 99.5% of onsets are detected within 10 ms and 30 ms, respectively, of the true onsets. The algorithms performance in spite of the large degree of variation in signal quality and waveform morphology present in the test data suggests that it may serve as a valuable tool for the accurate and reliable identification of CBFV pulse onsets in neurocritical care settings.

bioinformatics↗

bioRxiv2018

Tristetraprolin/ZFP36 regulates the turnover of autoimmune-associated HLA-DQ mRNAs

We have previously demonstrated that the expression of HLA class II genes is regulated by the binding of a ribonucleoprotein complex that affects the mRNA processing. We identified protein components of a complex binding transcripts encoding the HLA-DR molecule. Here we investigate whether the same RNA binding proteins interact with 3UTR of mRNAs encoding the HLA-DQ isotype. Specifically, we focused on the HLA-DQ2.5 molecule, expressed on the surface of antigen presenting cells, and representing the main susceptibility factor for celiac disease (CD). This molecule, encoded by HLA-DQA1*05 and HLA-DQB1*02 alleles, presents the antigenic gluten peptides to CD4+ T lymphocytes, activating the autoimmune response.\n\nHere, we identified an additional component of the RNP complex, Tristetraprolin (TTP) or ZFP36, a zinc-finger protein, widely described as a factor modulating mRNA stability. TTP shows high affinity binding to 3UTR of CD-associated HLA-DQA1*05 and HLA-DQB1*02 alleles, in contrast to lower affinity binding to HLA-DQA1*01 and HLA-DQB1*05 non-CD associated alleles. Our in silico analysis, confirmed by molecular experiments, demonstrates that TTP specifically modulates the stability of the transcripts associated with celiac disease.

molecular biology↗

bioRxiv2018

Molecular definition of group 1 innate lymphoid cells in the mouse uterus

Determining the function of uterine lymphocytes is challenging because of the rapidly changing nature of the organ in response to sex hormones and, during pregnancy, to the invading fetal trophoblast cells. Here we provide the first genome-wide transcriptome atlas of mouse uterine group 1 innate lymphoid cells (g1 ILCs) at mid-gestation. The composition of g1 ILCs fluctuates throughout reproductive life, with Eomes-veCD49a+ ILC1s dominating before puberty and specifically expanding in second pregnancies, when the expression of CXCR6, a marker of memory cells, is upregulated. Tissue-resident Eomes+CD49a+ NK cells (trNK), which resemble human uterine NK cells, are most abundant during early pregnancy, and showcase gene signatures of responsiveness to TGF-{beta}, connections with trophoblast, epithelial, endothelial and smooth muscle cells, leucocytes, as well as extracellular matrix. Unexpectedly, trNK cells express genes involved in anaerobic glycolysis, lipid metabolism, iron transport, protein ubiquitination, and recognition of microbial molecular patterns. Conventional NK cells expand late in gestation and may engage in crosstalk with trNK cells involving IL-18 and IFN-{gamma}. These results identify trNK cells as the cellular hub of uterine g1 ILCs at mid-gestation and mark CXCR6+ ILC1s as potential memory cells of pregnancy.

immunology↗

bioRxiv2017

Estimating the footprint of pollution on coral reefs using models of species turn-over

Ecological communities typically change along gradients of human impact, though it is difficult to estimate the footprint of impacts for diffuse threats like pollution. Here we develop a joint model of benthic habitats on lagoonal coral reefs and use it to infer change in benthic composition along a gradient of distance from logging operations. The model estimates both changes in abundances of benthic groups and their compositional turn-over, a type of beta-diversity. We detect compositional turnover across the gradient and use the model to predict the footprint of turbidity impacts from logging. We then apply the model to predict impacts of recent logging activities, finding recent impacts to be small, because recent logging has occurred far from lagoonal reefs. Our model can be used more generally to estimate the footprint of human impacts on ecosystems and evaluate the benefits of conservation actions for ecosystems.

ecology↗