Biology subjects

Kleinman, A.

Publications and source records attributed to Kleinman, A..

9 recordsLinked to original sources

bioRxiv2025

Evaluation of antibiotic and peptide vaccine strategies for mirror bacterial infections

Recent advances in synthetic biology have raised concerns that the creation of bacteria composed completely of mirror-image biomolecules may be possible in the coming decades. Such "mirror bacteria" could pose an unprecedented biosecurity risk, as they are predicted to be highly virulent pathogens resulting from severe immune evasion. Pharmaceutical interventions, including antibiotics and vaccines, could likely provide some limited protection in the event of a mirror bacterial outbreak. Understanding the feasibility of specific pharmaceutical antimirror strategies may help inform the appropriate measures to confront the risks of mirror bacteria. Here, we experimentally evaluated the prospects of previously proposed antimirror antibiotic and vaccine strategies. First, we assessed the expected efficacy of existing antibiotics chloramphenicol, linezolid, tedizolid, and aztreonam against mirror bacteria by characterizing the antibacterial activities of their enantiomers against natural-chirality bacteria. We found that ent-chloramphenicol, ent-linezolid, ent-tedizolid, and ent-aztreonam exhibited minimal antibiotic activity, suggesting that their parent antibiotics would be ineffective against mirror bacterial infections. Second, to explore whether the enantiomers of existing antibiotics could be suitable as antimirror antibiotics, we evaluated the acute toxicities of ent-chloramphenicol, ent-linezolid, ent-tedizolid, and ent-aztreonam in mice, finding that these compounds have favorable acute toxicity profiles compatible with their continued development. Finally, we investigated D-peptide-based approaches to antimirror vaccines, finding that three bacterially-derived D-peptides induced robust D-peptide-specific antibody responses in mice when conjugated to a carrier protein and adjuvanted. Our results support previous suggestions that the enantiomers of existing antibiotics and D-peptide conjugate vaccines represent feasible pharmaceutical strategies against mirror bacterial infections. IMPORTANCETechnologies enabling the creation of mirror bacteria--bacteria constructed of molecules that are mirror images of those found in nature--may be on the horizon. If created, mirror bacteria would likely pose an unprecedented risk to life on earth given their evasion of natural immune responses. Although they would not protect against widespread environmental damage, antibiotics and vaccines could provide some limited protection to human populations in the event of a mirror bacterial outbreak. We experimentally assessed the prospects of three antimirror strategies: repurposing existing antibiotics, developing mirror versions of existing antibiotics, and developing vaccines based on mirror-image peptides. We broadly conclude that many existing antibiotics are unlikely to be effective against mirror bacteria, while the mirror images of existing antibiotics and mirror-image peptides could serve as foundations for antimirror antibiotics and vaccines, respectively. Our findings may help inform discussions on the proper role of medical countermeasures to defend against mirror bacteria.

microbiology↗

bioRxiv2025

An Updated Polygenic Index Repository: Expanded Phenotypes, New Cohorts, and Improved Causal Inference

Polygenic indexes (PGIs) -- DNA-based predictors of individual phenotypes -- have become essential tools across biomedical and social sciences. We introduce Version 2 of the Polygenic Index Repository, which expands phenotype coverage from 47 to 61, increases the number of participating datasets from 11 to 20, and adopts a more consistent and improved methodology for PGI construction. For 16 phenotypes, we leverage summary statistics from an updated GWAS meta-analysis with greater statistical power compared to the original release, thereby improving the PGIs predictive power. To improve power for family-based analyses, we provide imputed parental PGIs in all datasets with first-degree relatives and offer a framework for interpreting results from analyses that control for parental PGIs. We illustrate the utility of parental PGIs using two applications: (1) comparing PGI associations with and without parental PGI controls for all phenotypes in two Repository datasets with family data, and (2) for BMI and diastolic blood pressure, exploring the contribution of causal versus non-causal components of PGI associations to the imperfect portability of PGIs across subgroups within a genetic ancestry. Collectively, the updates enhance predictive performance, broaden the Repositorys scope, and introduce novel resources that reduce confounding bias and improve interpretability.

genomics↗

bioRxiv2023

Collection of Biospecimens from the Inspiration4 Mission Establishes the Standards for the Space Omics and Medical Atlas (SOMA)

The SpaceX Inspiration4 mission provided a unique opportunity to study the impact of spaceflight on the human body. Biospecimen samples were collected from the crew at different stages of the mission, including before (L-92, L-44, L-3 days), during (FD1, FD2, FD3), and after (R+1, R+45, R+82, R+194 days) spaceflight, creating a longitudinal sample set. The collection process included samples such as venous blood, capillary dried blood spot cards, saliva, urine, stool, body swabs, capsule swabs, SpaceX Dragon capsule HEPA filter, and skin biopsies, which were processed to obtain aliquots of serum, plasma, extracellular vesicles, and peripheral blood mononuclear cells. All samples were then processed in clinical and research laboratories for optimal isolation and testing of DNA, RNA, proteins, metabolites, and other biomolecules. This paper describes the complete set of collected biospecimens, their processing steps, and long-term biobanking methods, which enable future molecular assays and testing. As such, this study details a robust framework for obtaining and preserving high-quality human, microbial, and environmental samples for aerospace medicine in the Space Omics and Medical Atlas (SOMA) initiative, which can also aid future experiments in human spaceflight and space biology.

molecular biology↗

bioRxiv2023

Tetravalent SARS-CoV-2 S1 Subunit Protein Vaccination Elicits Robust Humoral and Cellular Immune Responses in SIV-Infected Rhesus Macaque Controllers

The COVID-19 pandemic has highlighted the need for safe and effective vaccines to be rapidly developed and distributed worldwide, especially considering the emergence of new SARS-CoV-2 variants. Protein subunit vaccines have emerged as a promising approach due to their proven safety record and ability to elicit robust immune responses. In this study, we evaluated the immunogenicity and efficacy of an adjuvanted tetravalent S1 subunit protein COVID-19 vaccine candidate composed of the Wuhan, B.1.1.7 variant, B.1.351 variant, and P.1 variant spike proteins in a nonhuman primate model with controlled SIVsab infection. The vaccine candidate induced both humoral and cellular immune responses, with T- and B cell responses mainly peaking post-boost immunization. The vaccine also elicited neutralizing and cross-reactive antibodies, ACE2 blocking antibodies, and T-cell responses, including spike specific CD4+ T cells. Importantly, the vaccine candidate was able to generate Omicron variant spike binding and ACE2 blocking antibodies without specifically vaccinating with Omicron, suggesting potential broad protection against emerging variants. The tetravalent composition of the vaccine candidate has significant implications for COVID-19 vaccine development and implementation, providing broad antibody responses against numerous SARS-CoV-2 variants.

immunology↗

bioRxiv2021

The Kishony Mega-Plate Experiment, a Markov Process

A correct understanding of the DNA evolution of drug resistance is critical in developing strategies for suppressing and preventing this process. The Kishony Mega-Plate Experiment demonstrates this important phenomenon that occurs in the practice of medicine, that of the evolution of drug-resistance. The evolutionary process which the bacteria in this experiment are doing is called a Markov Process or Markov Chain. Understanding this process enables clinicians and researchers to predict the evolution of drug-resistance and develop strategies to prevent this process. This paper will show how to apply the Markov Chain model of DNA evolution to the Kishony Mega-Plate Experiment and why the experiment behaves the way it does by contrasting the Jukes-Cantor model of DNA evolution (a stationary model) with a modification of the Jukes-Cantor model that makes it a non-stationary, non-equilibrium Markov Chain. The numerical behaviors of the stationary and non-stationary models are compared. What this analysis shows is that DNA evolution is a non-stationary, non-equilibrium process and that by using the correct non-stationary, non-equilibrium model that one can simulate and predict the behavior of real evolutionary examples and that these analytical tools can give the clinician guidance on how to use antimicrobial selection pressures for treating infectious diseases. This in turn can help reduce the numbers and costs of hospitalization for sepsis, pneumonia and other infectious diseases.

evolutionary biology↗

bioRxiv2021

Resource Profile and User Guide of the Polygenic Index Repository

Polygenic indexes (PGIs) are DNA-based predictors. Their value for research in many scientific disciplines is rapidly growing. As a resource for researchers, we used a consistent methodology to construct PGIs for 47 phenotypes in 11 datasets. To maximize the PGIs prediction accuracies, we constructed them using genome-wide association studies--some of which are novel--from multiple data sources, including 23andMe and UK Biobank. We present a theoretical framework to help interpret analyses involving PGIs. A key insight is that a PGI can be understood as an unbiased but noisy measure of a latent variable we call the "additive SNP factor." Regressions in which the true regressor is the additive SNP factor but the PGI is used as its proxy therefore suffer from errors-in-variables bias. We derive an estimator that corrects for the bias, illustrate the correction, and make a Python tool for implementing it publicly available.

genomics↗

bioRxiv2019

Human loss-of-function variants suggest that partial LRRK2 inhibition is a safe therapeutic strategy for Parkinsons disease

Human genetic variants causing loss-of-function (LoF) of protein-coding genes provide natural in vivo models of gene inactivation, which are powerful indicators of gene function and the potential toxicity of therapeutic inhibitors targeting these genes1,2. Gain-of-kinase-function variants in LRRK2 are known to significantly increase the risk of Parkinsons disease3,4, suggesting that inhibition of LRRK2 kinase activity is a promising therapeutic strategy. Whilst preclinical studies in model organisms have raised some on-target toxicity concerns5-8, the biological consequences of LRRK2 inhibition have not been well characterized in humans. Here we systematically analyse LoF variants in LRRK2 observed across 141,456 individuals sequenced in the Genome Aggregation Database (gnomAD)9 and over 4 million participants in the 23andMe genotyped dataset, to assess their impact at a molecular and phenotypic level. After thorough variant curation, we identify 1,358 individuals with high-confidence predicted LoF variants in LRRK2, several with experimental validation. We show that heterozygous LoF of LRRK2 reduces LRRK2 protein level by ~50% but is not associated with reduced life expectancy, or with any specific phenotype or disease state. These data suggest that therapeutics that downregulate LRRK2 levels or kinase activity by up to 50% are unlikely to have major on-target safety liabilities. Our results demonstrate the value of large scale genomic databases and phenotyping of human LoF carriers for target validation in drug discovery.

genomics↗

bioRxiv2018

An Atlas of Human and Murine Genetic Influences on Osteoporosis

Osteoporosis is a common debilitating chronic disease diagnosed primarily using bone mineral density (BMD). We undertook a comprehensive assessment of human genetic determinants of bone density in 426,824 individuals, identifying a total of 518 genome-wide significant loci, (301 novel), explaining 20% of the total variance in BMD--as estimated by heel quantitative ultrasound (eBMD). Next, meta-analysis identified 13 bone fracture loci in ~1.2M individuals, which were also associated with BMD. We then identified target genes from cell-specific genomic landscape features, including chromatin conformation and accessible chromatin sites, that were strongly enriched for genes known to influence bone density and strength (maximum odds ratio = 58, P = 10-75). We next performed rapid throughput skeletal phenotyping of 126 knockout mice lacking eBMD Target Genes and showed that these mice had an increased frequency of abnormal skeletal phenotypes compared to 526 unselected lines (P < 0.0001). In-depth analysis of one such Target Gene, DAAM2, showed a disproportionate decrease in bone strength relative to mineralization. This comprehensive human and murine genetic atlas provides empirical evidence testing how to link associated SNPs to causal genes, offers new insights into osteoporosis pathophysiology and highlights opportunities for drug development.

genomics↗

bioRxiv2018

Genome-wide study identifies 611 loci associated with risk tolerance and risky behaviors

Humans vary substantially in their willingness to take risks. In a combined sample of over one million individuals, we conducted genome-wide association studies (GWAS) of general risk tolerance, adventurousness, and risky behaviors in the driving, drinking, smoking, and sexual domains. We identified 611 approximately independent genetic loci associated with at least one of our phenotypes, including 124 with general risk tolerance. We report evidence of substantial shared genetic influences across general risk tolerance and risky behaviors: 72 of the 124 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is moderately to strongly genetically correlated ([Formula] to 0.50) with a range of risky behaviors. Bioinformatics analyses imply that genes near general-risk-tolerance-associated SNPs are highly expressed in brain tissues and point to a role for glutamatergic and GABAergic neurotransmission. We find no evidence of enrichment for genes previously hypothesized to relate to risk tolerance.

genetics↗