Biology subjects

Jojic, V.

Publications and source records attributed to Jojic, V..

9 recordsLinked to original sources

bioRxiv2024

Longitudinal analysis of body weight reveals homeostatic and adaptive traits linked to lifespan in diversity outbred mice

Dense temporal measurements of physiological health using simple and consistent assays are essential to characterize biological processes associated with aging and evaluate the effectiveness of interventions on these processes. We measured body weight in 960 genetically diverse mice, every 7-10 days over the full course of their lifespan. We used a state space model to characterize the trajectories of body weight throughout life and derived 10 novel traits capturing the dynamics of body weight that are both associated with lifespan and heritable. Genetic mapping of these traits identified 12 genomic loci, none of which were previously mapped to body weight. We observed that the ability to stabilize body weight, despite fluctuations in energy intake and expenditure, is positively associated with lifespan and mapped to a genomic locus linked to energy homeostasis. Our results highlight the importance of dense longitudinal measurements of physiological traits for monitoring health and aging.

physiology↗

bioRxiv2021

Automated, high-dimensional evaluation of physiological aging and resilience in outbred mice

Behavior and physiology are essential readouts in many studies but have not benefited from the high-dimensional data revolution that has transformed molecular and cellular phenotyping. To address this, we developed an approach that combines commercially available automated phenotyping hardware with a systems biology analysis pipeline to generate a high-dimensional readout of mouse behavior/physiology, as well as intuitive and health-relevant summary statistics (resilience and biological age). We used this platform to longitudinally evaluate aging in hundreds of outbred mice across an age range from 6 months to 3.4 years. In contrast to the assumption that aging can only be measured at the limits of animal ability via challenge-based tasks, we observed widespread physiological and behavioral aging starting in early life. Using network connectivity analysis, we found that organism-level resilience exhibited an accelerating decline with age that was distinct from the trajectory of individual phenotypes. We developed a method, Combined Aging and Survival Prediction of Aging Rate (CASPAR), for jointly predicting chronological age and survival time and showed that the resulting model is able to predict both variables simultaneously, a behavior that is not captured by separate age and mortality prediction models. This study provides a uniquely high-resolution view of physiological aging in mice and demonstrates that systems-level analysis of physiology provides insights not captured by individual phenotypes. The approach described here allows aging, and other processes that affect behavior and physiology, to be studied with sophistication and rigor.

systems biology↗

bioRxiv2020

Precise Estimation of In Vivo Protein Turnover Rates

Isotopic labeling with deuterium oxide (D2O) is a common technique for estimating in vivo protein turnover, but its use has been limited by two long-standing problems: (1) identifying non-monoisotopic peptides; and (2) estimating protein turnover rates in the presence of dynamic amino acid enrichment. In this paper, we present a novel experimental and analytical framework for solving these two problems. Peptides with high probabilities of labeling in many amino acids present fragmentation spectra that frequently do not match the theoretical spectra used in standard identification algorithms. We resolve this difficulty using a modified search algorithm we call Conditional Ion Distribution Search (CIDS). Increased identifications from CIDS along with direct measurement of amino acid enrichment and statistical modeling that accounts for heterogeneous information across peptides, dramatically improves the accuracy and precision of half-life estimates. We benchmark the approach in cells, where near-complete labeling is possible, and conduct an in vivo experiment revealing, for the first time, differences in protein turnover between mice and naked mole-rats commensurate with their disparate longevity.

bioinformatics↗

bioRxiv2020

Age and diet shape the genetic architecture of body weight in Diversity Outbred mice

AO_SCPLOWBSTRACTC_SCPLOWUnderstanding how genetic variation shapes an age-dependent complex trait relies on accurate quantification of both the additive genetic effects and genotype-environment interaction effects in an age-dependent manner. We used a generalization of the linear mixed model to quantify diet-dependent genetic contributions to body weight and growth rate measured from early development through adulthood of 960 Diversity Outbred female mice subjected to five dietary interventions. We observed that heritability of body weight remained substantially high (h2 {approx} 0.8) throughout adulthood under the 40% calorie restriction diet, while heritability, although still appreciably high, declined with age under all other dietary regimes. We identified 14 loci significantly associated with body weight in an age-dependent manner and 19 loci that contribute to body weight in an age- and diet-dependent manner. We found the effect of body weight alleles to be dynamic with respect to genomic background, age, and diet, identifying the scope of pleiotropy and several instances of allelic heterogeneity. In many cases, we fine-mapped these loci to narrow genomic intervals containing a few genes and impute putative functional variants from the genome sequence of the DO founders. Of the loci associated with body weight in a diet-dependent manner, many have been previously linked to neurological function and behavior in mice or humans. These results enable us to more fully understand the dynamics of the genetic architecture of body weight with age and in response to different dietary interventions, and to predict the effectiveness of dietary intervention on overall health in distinct genetic backgrounds.

genetics↗

bioRxiv2020

Multiplexed imaging of human tuberculosis granulomas uncovers immunoregulatory features conserved across tissue and blood

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis that is distinctly characterized by granuloma formation within infected tissues. Granulomas are dynamic and organized immune cell aggregates that limit dissemination, but can also hinder bacterial clearance. Consequently, outcome in TB is influenced by how granuloma structure and composition shift the balance between these two functions. To date, our understanding of what factors drive granuloma function in humans is limited. With this in mind, we used Multiplexed Ion Beam Imaging by Time-of-Flight (MIBI-TOF) to profile 37 proteins in tissues from thirteen patients with active TB disease from the U.S. and South Africa. With this dataset, we constructed a comprehensive tissue atlas where the lineage, functional state, and spatial distribution of 19 unique cell subsets were mapped onto eight phenotypically-distinct granuloma microenvironments. This work revealed an immunosuppressed microenvironment specific to TB granulomas with spatially coordinated co-expression of IDO1 and PD-L1 by myeloid cells and proliferating regulatory T cells. Interestingly, this microenvironment lacked markers consistent with T-cell activation, supporting a myeloid-mediated mechanism of immune suppression. We observed similar trends in gene expression of immunoregulatory proteins in a confirmatory transcriptomic analysis of peripheral blood collected from over 1500 individuals with latent or active TB infection and healthy controls across 29 cohorts spanning 14 countries. Notably, PD-L1 gene expression was found to correlate with TB progression and treatment response, supporting its potential use as a blood-based biomarker. Taken together, this study serves as a framework for leveraging independent cohorts and complementary methodologies to understand how local and systemic immune responses are linked in human health and disease.

immunology↗

bioRxiv2019

An Inflammatory Clock Predicts Multi-morbidity, Immunosenescence and Cardiovascular Aging in Humans

While many diseases of aging have been linked to the immunological system, immune metrics with which to identify the most at-risk individuals are lacking. Here, we studied the blood immunome of 1001 individuals age 8-96 and derived an inflammatory clock of aging (iAge), which tracked with multi-morbidity and immunosenescence. In centenarians, iAge was on average, 40 years lower than their corresponding chronological age. The strongest contributor to this metric was the chemokine CXCL9, which was involved in cardiac aging, affected vascular function, and down-regulated Sirtuin-3, a longevity-associated molecule. Thus, our results identify an important link between inflammatory molecules and pathways known to govern lifespan.

immunology↗

bioRxiv2019

Single-cell transcriptomics of the naked mole-rat reveals unexpected features of mammalian immunity

Using single-cell transcriptional profiling we mapped the immune system of the naked mole-rat (Heterocephalus glaber), a small but long-lived and cancer-resistant subterranean rodent. Both splenic and circulating immune cells were examined in healthy young animals and following an infection-mimicking lipopolysaccharide challenge. Our study revealed that the naked mole-rat immune system is characterized by a high myeloid to lymphoid cell ratio that includes a novel, lipopolysaccharide responsive, granulocyte cell subset not found in the mouse. Conversely, we find that naked mole-rats do not have a cell subset that corresponds to natural killer cells as defined in other well-characterized mammalian species. Supporting this finding, we show that the naked mole-rat genome has not expanded any of the gene families encoding diverse natural killer cell receptors, which are the genomic hallmarks of species in which natural killer cells have been described. These unusual features suggest an atypical mode of immunosurveillance and a greater reliance on myeloid-biased innate immunity.

immunology↗

bioRxiv2018

Conservation and divergence in modules of the transcriptional programs of the human and mouse immune systems

Studies in mouse have shed important light on human hematopoietic differentiation and disease. However, substantial differences between the two species often limit the translation of findings from mouse to human.\n\nHere, we compare previously defined modules of co-expressed genes in human and mouse immune cells based on compendia of genome-wide profiles. We show that the overall modular organization of the transcriptional program is conserved. We highlight modules of co-expressed genes in one species that dissolve or split in the other species. Many of the associated regulatory mechanisms - as reflected by computationally inferred trans regulators, or enriched cis-regulatory elements - are conserved between the species. Nevertheless, the degree of conservation in regulatory mechanism is lower than that of expression, suggesting that distinct regulation may underlie some of the conserved transcriptional responses.

bioinformatics↗

bioRxiv2017

Efficient online-group-screening designs for agent identification

Identifying significant causal agents among a large number of candidates is challenging. When experimental resources are limited, exhaustively screening a large number of agents for the desired effect could incur a large cost and take a substantial amount of time. However, in many large scale experiments, such as high-throughput screening (HTS), the ratio of causal to non-causal agents is usually very low.\n\nIn this paper, we introduce a group-screening strategy to efficiently screen causal agents by grouping them into treatments. Our analysis shows that when a large number of candidates factors are screened and true agent percentage is very low (less than 1%), even in the worst case we could save up to 80% of the experiment runs. In the case where experiments span many rounds, we provide an online version of the group-screening that can determine the best strategy automatically based on the existing results. We applied this method to a real HTS experiment with 50,000 candidates that would require 9 rounds to finish in an exhaustive case. Our analysis showed that by applying the online-group-screening method, in the worst case, we can use 3 rounds and 19.7% (9828/50000) total tests to identify all the agents.\n\nFinally, we show that with minor modifications, this framework extends to more complex agent discovery problems.

bioinformatics↗