Publications by authors named "Joseph Bielawski"

Gigantism is prevalent in animals, but it has never reached more extreme levels than in aquatic mammals such as whales, dolphins, and porpoises. A new study by Silva et al. has uncovered five genes underlying this gigantism, a phenotype with important connections to aging and cancer suppression in long-lived animals.

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Introduction: Most children with leukemia and lymphoma experience febrile neutropenia. These are treated with empiric antibiotics that include β-lactams and/or vancomycin. These are often administered for extended periods, and the effect on the resistome is unknown.

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Understanding community-level selection using Lewontin's criteria requires both community-level inheritance and community-level heritability, and in the discipline of community and ecosystem genetics, these are often conflated. While there are existing studies that show the possibility of both, these studies impose community-level inheritance as a product of the experimental design. For this reason, these experiments provide only weak support for the existence of community-level selection in nature.

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Background And Aims: Nutritional therapy with the Crohn's Disease Exclusion Diet + Partial Enteral Nutrition [CDED+PEN] or Exclusive Enteral Nutrition [EEN] induces remission and reduces inflammation in mild-to-moderate paediatric Crohn's disease [CD]. We aimed to assess if reaching remission with nutritional therapy is mediated by correcting compositional or functional dysbiosis.

Methods: We assessed metagenome sequences, short chain fatty acids [SCFA] and bile acids [BA] in 54 paediatric CD patients reaching remission after nutritional therapy [with CDED + PEN or EEN] [NCT01728870], compared to 26 paediatric healthy controls.

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Due to decreased immunity, both antibiotics and antifungals are regularly used in pediatric hematologic-cancer patients as a means to prevent severe infections and febrile neutropenia. The general effect of antibiotics on the human gut microbiome is profound, yielding decreased diversity and changes in community structure. However, the specific effect on pediatric oncology patients is not well-studied.

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Undergraduate students from underrepresented backgrounds (e.g., Black, Indigenous, and people of color [BIPOC], members of the Deaf community, people with disabilities, members of the 2SLGBTQIA+ community, from low-income backgrounds, or underrepresented genders) continue to face exclusion and marginalization in higher education.

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Survival analysis is a prolific statistical tool in medicine for inferring risk and time to disease-related events. However, it is underutilized in microbiome research to predict microbial community-mediated events, partly due to the sparsity and high-dimensional nature of the data. We advance the application of Cox proportional hazards (Cox PH) survival models to environmental DNA (eDNA) data with feature selection suitable for filtering irrelevant and redundant taxonomic variables.

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Site-specific amino acid preferences are influenced by the genetic background of the protein. The preferences for resident amino acids are expected to, on average, increase over time because of replacements at other sites-a nonadaptive phenomenon referred to as the "evolutionary Stokes shift." Alternatively, decreases in resident amino acid propensity have recently been viewed as evidence of adaptations to external environmental changes.

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Amino acid preferences vary across sites and time. While variation across sites is widely accepted, the extent and frequency of temporal shifts are contentious. Our understanding of the drivers of amino acid preference change is incomplete: To what extent are temporal shifts driven by adaptive versus nonadaptive evolutionary processes? We review phenomena that cause preferences to vary (e.

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Treatment of pediatric acute lymphoblastic leukemia (ALL) with pegaspargase exploits ALL cells dependency on asparagine. Pegaspargase depletes asparagine, consequentially affecting aspartate, glutamine and glutamate. The gut as a confounding source of these amino acids (AAs) and the role of gut microbiome metabolism of AAs has not been examined.

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Fitness contribution alone should not be the criterion of 'function' in molecular biology and genomics. Disagreement over the use of 'function' in molecular biology and genomics is still with us, almost eight years after publicity surrounding the Encyclopedia of DNA Elements project claimed that 80.4% of the human genome comprises "functional elements".

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Asparaginase (ASNase) is an effective treatment of pediatric acute lymphoblastic leukemia (ALL). Changes in ASNase activity may lead to suboptimal treatment and poorer outcomes. The gut microbiome produces metabolites that could impact ASNase therapy, however, remains uninvestigated.

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Do interactions between residues in a protein (i.e., epistasis) significantly alter evolutionary dynamics? If so, what consequences might they have on inference from traditional codon substitution models which assume site-independence for the sake of computational tractability? To investigate the effects of epistasis on substitution rates, we employed a mechanistic mutation-selection model in conjunction with a fitness framework derived from protein stability.

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Human genome-wide association studies (GWASs) have recurrently estimated lower heritability estimates than familial studies. Many explanations have been suggested to explain these lower estimates, including that a substantial proportion of genetic variation and gene-by-environment interactions are unmeasured in typical GWASs. The human microbiome is potentially related to both of these explanations, but it has been more commonly considered as a source of unmeasured genetic variation.

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The Estuary and Gulf of St. Lawrence (EGSL) in eastern Canada are among the largest and most productive coastal ecosystems in the world. Very little information on bacterial diversity exists, hampering our understanding of the relationships between bacterial community structure and biogeochemical function in the EGSL.

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Background: The gut microbiome is extensively involved in induction of remission in pediatric Crohn's disease (CD) patients by exclusive enteral nutrition (EEN). In this follow-up study of pediatric CD patients undergoing treatment with EEN, we employ machine learning models trained on baseline gut microbiome data to distinguish patients who achieved and sustained remission (SR) from those who did not achieve remission nor relapse (non-SR) by 24 weeks.

Methods: A total of 139 fecal samples were obtained from 22 patients (8-15 years of age) for up to 96 weeks.

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Gut microbiome community structure is associated with Crohn's disease (CD) development and response to therapy. Bile acids (BAs) play a central role in modulating intestinal immune responses, and changes in gut bacterial communities can profoundly alter the intestinal BA pool. The liver synthesizes and conjugates primary bile acids (priBAs) that are then deconjugated, epimerized, and dehydroxylated by gut bacteria to produce secondary bile acids (secBAs).

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A central objective in biology is to link adaptive evolution in a gene to structural and/or functional phenotypic novelties. Yet most analytic methods make inferences mainly from either phenotypic data or genetic data alone. A small number of models have been developed to infer correlations between the rate of molecular evolution and changes in a discrete or continuous life history trait.

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Codon substitution models (CSMs) are commonly used to infer the history of natural section for a set of protein-coding sequences, often with the explicit goal of detecting the signature of positive Darwinian selection. However, the validity and success of CSMs used in conjunction with the maximum likelihood (ML) framework is sometimes challenged with claims that the approach might too often support false conclusions. In this chapter, we use a case study approach to identify four legitimate statistical difficulties associated with inference of evolutionary events using CSMs.

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Organisms display astonishing levels of cell and molecular diversity, including genome size, shape, and architecture. In this chapter, we review how the genome can be viewed as both a structural and an informational unit of biological diversity and explicitly define our intended meaning of genetic information. A brief overview of the characteristic features of bacterial, archaeal, and eukaryotic cell types and viruses sets the stage for a review of the differences in organization, size, and packaging strategies of their genomes.

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Background: Testing model adequacy is important before a DNA substitution model is chosen for phylogenetic inference. Using a mis-specified model can negatively impact phylogenetic inference, for example, the maximum likelihood method can be inconsistent when the DNA sequences are generated under a tree topology which is in the Felsentein Zone and analyzed with a mis-specified or inadequate model. However, model adequacy testing in phylogenetics is underdeveloped.

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Background & Aims: Exclusive enteral nutrition (EEN) is recommended for children with mild to moderate Crohn's disease (CD), but implementation is challenging. We compared EEN with the CD exclusion diet (CDED), a whole-food diet coupled with partial enteral nutrition (PEN), designed to reduce exposure to dietary components that have adverse effects on the microbiome and intestinal barrier.

Methods: We performed a 12-week prospective trial of children with mild to moderate CD.

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Background: An excess of nonsynonymous substitutions, over neutrality, is considered evidence of positive Darwinian selection. Inference for proteins often relies on estimation of the nonsynonymous to synonymous ratio (ω = d/d) within a codon model. However, to ease computational difficulties, ω is typically estimated assuming an idealized substitution process where (i) all nonsynonymous substitutions have the same rate (regardless of impact on organism fitness) and (ii) instantaneous double and triple (DT) nucleotide mutations have zero probability (despite evidence that they can occur).

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Motivation: Likelihood ratio tests are commonly used to test for positive selection acting on proteins. They are usually applied with thresholds for declaring a protein under positive selection determined from a chi-square or mixture of chi-square distributions. Although it is known that such distributions are not strictly justified due to the statistical irregularity of the problem, the hope has been that the resulting tests are conservative and do not lose much power in comparison with the same test using the unknown, correct threshold.

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Microbial samples taken from an environment often represent mixtures of communities, where each community is composed of overlapping assemblages of species. Such data represent a serious analytical challenge, as the community structures will be present as complex mixtures, there will be very large numbers of component species, and the species abundance will often be sparse over samples. The structure and complexity of these samples will vary according to both biotic and abiotic factors, and classical methods of data analysis will have a limited value in this setting.

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