Biology subjects

Li, J. Z.

Publications and source records attributed to Li, J. Z..

34 records · Page 2Linked to original sources

bioRxiv2021

Placental expression of ACE2 and TMPRSS2 in maternal SARS-CoV-2 infection: are placental defenses mediated by fetal sex?

BackgroundSex differences in vulnerability to and severity of SARS-CoV-2 infection have been described in non-pregnant populations. ACE2 and TMPRSS2, host molecules required for viral entry, are regulated by sex steroids and expressed in the placenta. We sought to investigate whether placental ACE2 and TMPRSS2 expression vary by fetal sex and in the presence of maternal SARS-CoV-2 infection. MethodsPlacental ACE2 and TMPRSS2 were quantified in 68 pregnant individuals (38 SARS-CoV-2 positive, 30 SARS-CoV-2 negative) delivering at Mass General Brigham from April to June 2020. Maternal SARS-CoV-2 status was determined by nasopharyngeal RT-PCR. Placental SARS-CoV-2 viral load was quantified. RTqPCR was performed to quantify expression of ACE2 and TMPRSS2 relative to the reference gene YWHAZ. Western blots were performed on placental homogenates to quantify protein levels. The impact of fetal sex and SARS-CoV-2 exposure on ACE2 and TMPRSS2 expression was analyzed by 2-way ANOVA. ResultsSARS-CoV-2 virus was undetectable in all placentas. Maternal SARS-CoV-2 infection impacted TMPRSS2 placental gene and protein expression in a sexually dimorphic fashion (2-way ANOVA interaction p-value: 0.002). We observed no impact of fetal sex or maternal SARS-CoV-2 status on placental ACE2 gene or protein expression. Placental TMPRSS2 expression was significantly correlated with ACE2 expression in males (Spearmans {rho}=0.54, p=0.02) but not females ({rho}=0.23, p=0.34) exposed to maternal SARS-CoV-2. ConclusionsSex differences in placental TMPRSS2 but not ACE2 were observed in the setting of maternal SARS-CoV-2 infection. These findings may have implications for offspring vulnerability to placental infection and vertical transmission.These findings may have implications for offspring vulnerability to placental infection and vertical transmission.

developmental biology↗

bioRxiv2021

Sexually dimorphic placental responses to maternal SARS-CoV-2 infection

There is a persistent male bias in the prevalence and severity of COVID-19 disease. Underlying mechanisms accounting for this sex difference remain incompletely understood. Interferon responses have been implicated as a modulator of disease in adults, and play a key role in the placental anti-viral response. Moreover, the interferon response has been shown to alter Fc-receptor expression, and therefore may impact placental antibody transfer. Here we examined the intersection of viral-induced placental interferon responses, maternal-fetal antibody transfer, and fetal sex. Placental interferon stimulated genes (ISGs), Fc-receptor expression, and SARS-CoV-2 antibody transfer were interrogated in 68 pregnancies. Sexually dimorphic placental expression of ISGs, interleukin-10, and Fc receptors was observed following maternal SARS-CoV-2 infection, with upregulation in males. Reduced maternal SARS-CoV-2-specific antibody titers and impaired placental antibody transfer were noted in pregnancies with a male fetus. These results demonstrate fetal sex-specific maternal and placental adaptive and innate immune responses to SARS-CoV-2.

immunology↗

bioRxiv2020

Profound Treg perturbations correlate with COVID-19 severity

The hallmark of severe COVID-19 disease has been an uncontrolled inflammatory response, resulting from poorly understood immunological dysfunction. We explored the hypothesis that perturbations in FoxP3+ T regulatory cells (Treg), key enforcers of immune homeostasis, contribute to COVID-19 pathology. Cytometric and transcriptomic profiling revealed a distinct Treg phenotype in severe COVID-19 patients, with an increase in both Treg proportions and intracellular levels of the lineage-defining transcription factor FoxP3, which correlated with poor outcomes. Accordingly, these Tregs over-expressed a range of suppressive effectors, but also pro-inflammatory molecules like IL32. Most strikingly, they acquired similarity to tumor-infiltrating Tregs, known to suppress local anti-tumor responses. These traits were most marked in acute patients with severe disease, but persisted somewhat in convalescent patients. These results suggest that Tregs may play nefarious roles in COVID-19, via suppressing anti-viral T cell responses during the severe phase of the disease, and/or via a direct pro-inflammatory role.

immunology↗

bioRxiv2020

Phospholipid Metabolism Is Associated with HIV Rebound Upon Treatment Interruption

Lipids are biologically active molecules involved in a variety of cellular processes and immunological functions, including inflammation. It was recently shown that phospholipids and their derivatives, lysophospholipids, can reactivate latent (dormant) tumor cells, causing cancer recurrence. However, the potential link between lipids and HIV latency, persistence, and viral rebound after cessation of antiretroviral therapy (ART) has never been investigated. We explored the links between plasma lipids and the burden of HIV during ART. We profiled the circulating lipidome from the plasma of 24 chronically HIV-infected individuals on suppressive ART who subsequently underwent an analytic treatment interruption (ATI) without concurrent immunotherapies. The pre-ATI viral burden was estimated as time-to-viral-rebound and viral load setpoints post-ATI. We found that higher pre-ATI levels of lysophospholipids, including the pro-inflammatory lysophosphatidylcholine, were associated with faster time-to-viral-rebound and higher viral setpoints upon ART cessation. Furthermore, higher pre-ATI levels of the pro-inflammatory byproduct of intestinal lysophosphatidylcholine metabolism, trimethylamine-N-oxide (TMAO), were also linked to faster viral rebound post-ART. Finally, pre-ATI levels of several phosphatidylcholine species (lysophosphatidylcholine precursors) correlated strongly with higher pre-ATI levels of HIV DNA in peripheral CD4+ T cells. Our proof-of-concept data point to phospholipids and lysophospholipids as plausible pro-inflammatory contributors to HIV persistence and rapid post-ART HIV rebound. The potential interplay between phospholipid metabolism and both the establishment and maintenance of HIV latent reservoirs during- and post-ART warrants further investigation. IMPORTANCEThe likelihood of HIV rebound after stopping antiretroviral therapy (ART) is a function of the interplay between the size of HIV reservoirs that persist despite ART and the host immunological and inflammatory factors that modulate these reservoirs. There is a need to comprehensively understand these host factors to develop a strategy to cure HIV infection and prevent viral rebound post-ART. Lipids are important biologically active molecules that are known to mediate several cellular functions, including reactivating latent tumor cells; however, their role in HIV latency, persistence, and post-ART rebound has never been investigated. We observed significant links between higher levels of the pro-inflammatory lysophosphatidylcholine and its intestinal metabolic byproduct, trimethylamine-N-oxide, and both faster time-to-viral rebound and higher viral load setpoint post ART. These data highlight the need for further studies to understand the potential contribution of phosphatidylcholine and lysophosphatidylcholine metabolism in shaping host immunological and inflammatory milieu during- and post-ART.

microbiology↗

bioRxiv2020

Prospective mapping of viral mutations that escape antibodies used to treat COVID-19

Antibodies are becoming a frontline therapy for SARS-CoV-2, but the risk of viral evolutionary escape remains unclear. Here we map how all mutations to SARS-CoV-2s receptor-binding domain (RBD) affect binding by the antibodies in Regenerons REGN-COV2 cocktail and Eli Lillys LY-CoV016. These complete maps uncover a single amino-acid mutation that fully escapes the REGN-COV2 cocktail, which consists of two antibodies targeting distinct structural epitopes. The maps also identify viral mutations that are selected in a persistently infected patient treated with REGN-COV2, as well as in lab viral escape selections. Finally, the maps reveal that mutations escaping each individual antibody are already present in circulating SARS-CoV-2 strains. Overall, these complete escape maps enable immediate interpretation of the consequences of mutations observed during viral surveillance.

microbiology↗

bioRxiv2020

Target lipidomics reveals associations between serum sphingolipids and insulin sensitivity by the glucose clamp

BackgroundThis study aimed to systematically investigate the associations between serum sphingolipids and insulin sensitivity as well as insulin secretion. This study also aimed to reveal potential predictors for insulin sensitivity or give perceptive insight into disease processes. MethodsWe conducted a lipidomics evaluation of molecularly distinct SPs in the serum of 86 consecutive Chinese adults with or without obesity and diabetes using electrospray ionization mass spectrometry coupled with liquid chromatography. The GIR30 was measured under steady conditions to assess insulin sensitivity by the gold standard hyperinsulinemic-euglycemic clamp. We created the ROC curves to detect the serum SMs diagnostic value and establish the diagnosis of insulin sensitivity. ResultsDifferential correlation network analysis illustrated correlations amongst lipids, insulin sensitivity, insulin secretion and other clinical indexes. Total and subspecies of serum SMs and globotriaosylceramides (Gb3s) were positively related to GIR30, free FAs (FFA 16:1, FFA20:4), some long chain GM3 and complex ceramide GluCers showed strong negative correlations with GIR30. Notably, ROC curves showed that SM/Cer and SM d18:0/26:0 may be good serum lipid predictors of diagnostic indicators of insulin sensitivity close to conventional clinical indexes such as 1/HOMA-IR (all areas under the curve >0.80) based on GIR30 as standard diagnostic criteria. ConclusionsThese results provide novel associations between serum sphingolipid between insulin sensitivity measured by the hyperinsulinemic-euglycemic clamp. We further identify two specific SPs that may represent prognostic biomarkers for insulin sensitivity.

physiology↗

bioRxiv2020

An enhanced isothermal amplification assay for viral detection

Rapid, inexpensive, robust diagnostics are essential to control the spread of infectious diseases. Current state of the art diagnostics are highly sensitive and specific, but slow, and require expensive equipment. We developed a molecular diagnostic test for SARS-CoV-2, FIND (Fast Isothermal Nucleic acid Detection), based on an enhanced isothermal recombinase polymerase amplification reaction. FIND has a detection limit on patient samples close to that of RT-qPCR, requires minimal instrumentation, and is highly scalable and cheap. It can be performed in high throughput, does not cross-react with other common coronaviruses, avoids bottlenecks caused by the current worldwide shortage of RNA isolation kits, and takes ~45 minutes from sample collection to results. FIND can be adapted to future novel viruses in days once sequence is available. One sentence summarySensitive, specific, rapid, scalable, enhanced isothermal amplification method for detecting SARS-CoV-2 from patient samples.

molecular biology↗

bioRxiv2019

Pan-cancer predictions of MEK inhibitor sensitivity are partially driven by between-tissue differences

Increased availability of drug response and genomics data for many tumor cell lines has accelerated the development of pan-cancer prediction models of drug response. However, it is unclear how much between-tissue differences in drug response and molecular characteristics may contribute to pan-cancer predictions. Also unknown is whether the performance of pan-cancer models could vary by cancer type. Here, we built a series of pan-cancer models using two datasets containing 346 and 504 cell lines with MEK inhibitor (MEKi) response and RNA, SNP, and CNV data, and found that, while the tissue-level drug responses are accurately predicted (between-tissue {rho}=0.88-0.98), only 5 of 10 cancer types showed successful within-tissue prediction performance (within-tissue {rho}=0.11-0.64). Between-tissue differences make substantial contributions to the performance of pan-cancer MEKi response predictions, as we estimate that exclusion of between-tissue signals leads to a 22% decrease in performance metrics. In practice, joint analysis of multiple cancer types usually has a larger sample size, hence greater power, than for one cancer type; and we observe that the higher accuracy of pan-cancer prediction of MEKi response is almost entirely due to the sample size advantage. Success of pan-cancer prediction reveals how drug response in different cancers may invoke shared regulatory mechanisms despite tissue-specific routes of oncogenesis, yet predictions in different cancer types require flexible incorporation of between-cancer and within-cancer signals. As most datasets in genome sciences contain multiple levels of heterogeneity, careful parsing of group characteristics and within-group, individual variation is essential when making robust inference.

cancer biology↗

bioRxiv2019

Viral rebound kinetics following single and combination immunotherapy for HIV/SIV

HIV infection can be treated but not cured with antiretroviral therapy, motivating the development of new therapies that instead target host immune responses. Three such immunotherapies were recently tested in non-human primates - a TLR7-agonist, therapeutic vaccine, and broadly-neutralizing antibody - and cured a subset of animals by preventing or controlling viral rebound after antiretrovirals were stopped. However, their mechanism of action remains unknown; for example, whether they reduced the pool of latently-infected cells versus boosted antiviral immunity, and whether they acted independently or synergistically. Here we conduct a detailed analysis of the kinetics of viral rebound after immunotherapy, and use mathematical models combined with rigorous statistical fitting to quantify the impact of these interventions on viral dynamics. We find that the vaccine reduced reactivation of latent virus by 4-fold, and boosted the avidity of antiviral immune responses by 17-fold when alone and 210-fold when combined with the TLR7-agonist. In the context of later initiation of antiretroviral therapy only, the TLR7-agonist reduced latent reservoir reactivation by 8-fold, but also slightly increased target cell availability (1.5-fold). The antibody boosted immune response avidity (8-fold) and displayed no detectable synergy with the TLR7-agonist. To predict the impact of these immunotherapies in clinical trials, we calibrated a model of HIV rebound to human treatment interruption trials and simulated the effect of adding each therapy. Overall, our results provide a framework for understanding the relative contributions of different mechanisms of preventing viral rebound and highlight the multifaceted roles of TLR7-agonists for HIV/SIV cure.

systems biology↗

bioRxiv2018

Coverage-based detection of copy number alterations in mixed samples using DNA sequencing data: a theoretical framework for evaluating statistical power

1DNA sequencing can discover not only single-base variants but also copy-number alterations (CNAs). In shotgun sequencing, regions of CNAs show step-wise changes in read depth when compared to adjacent \"normal\" regions, allowing their detection by parametric statistical tests that compare the mean coverage in suspected regions against that of a baseline distribution. Traditionally, the power of such a test depends on (1) the integer number of copy number change, (2) the overall sequencing depth, (3) the length of the CNA region, (4) the read length and (5) the variation of coverage along the genome, which depends on many experimental factors, including whether the chosen platform is whole-genome, whole-exome, or targeted-panel sequencing. In cases involving inadvertent sample mixing or genuine somatic mosaicism, power also depends on the mixing ratio. However, the analysis of statistical power that considers the interplay of all these factors has not been systematically developed. Here we present a general analytical framework and a series of simulations that explore situations from the simplest to the increasingly multifactorial. Specifically, we expand the expression of power to include not just the known factors but also one or both of two complications: (1) the dispersion of read depth around the mean beyond the independent sampling-by-sequencing assumption, and (2) the reduced fraction of the CNA-bearing sample (\"purity\") as seen in studies of intratumor heterogeneity or in clinical monitoring of minimal residual disease. We describe the analytical formula and their simplifications in special cases, and share the extendable scripts for others to perform customized power analysis using study-specific parameters. As study designs vary and technologies continue to evolve, the input data and the noise characteristics will change depending on the practical situation. We present two use cases commonly encountered in cancer research: ultra-shallow whole-genome sequencing for detecting large, chromosome-scale events, and targeted ultra-deep sequencing for surveillance of known CNAs in rare tumor clones in the task of sensitive detection of cancer relapse or metastasis. We also present an online calculator at https://shiny.med.umich.edu/apps/hanyou/CNV_Detection_Power_Calculator/.

bioinformatics↗

bioRxiv2018

Linkage disequilibrium connects genetic records of relatives typed with disjoint genomic marker sets

In familial searching in forensic genetics, a query DNA profile is tested against a database to determine whether it represents a relative of a database entrant. We examine the potential for using linkage disequilibrium to identify pairs of profiles as belonging to relatives when the query and database rely on nonoverlapping genetic markers. Considering data on individuals genotyped with both microsatellites used in forensic applications and genome-wide SNPs, we find that ~30-32% of parent-offspring pairs and ~35-36% of sib pairs can be identified from the SNPs of one member of the pair and the microsatellites of the other. The method suggests the possibility of performing familial searches of microsatellite databases using query SNP profiles, or vice versa. It also reveals that privacy concerns arising from computations across multiple databases that share no genetic markers in common entail risks not only for database entrants, but for their close relatives as well.

genetics↗

bioRxiv2018

Extended regions of suspected mis-assembly in the rat reference genome

We performed whole-genome sequencing for eight inbred rat strains commonly used in genetic mapping studies, and they are the founders of the NIH heterogeneous stock (HS) outbred colony. We provide their sequences and variant calls to the rat genomics community. When analyzing the variant calls we identified regions with unusually high heterozygosity. We show that these regions are consistent across the eight inbred strains, including the BN strain, which was the basis of the rat reference genome. These regions show significantly higher read depth than other regions in the genome. The evidence suggests that these regions may contain segmental duplications that are incorrectly overlaid in the reference genome. We provide masks for these suspected regions of mis-assembly as a resource for the community to flag potentially false interpretations of mapping results or functional data.

genomics↗

bioRxiv2018

Refinement of highly flexible protein structures using simulation-guided spectroscopy

Highly flexible proteins present a special challenge for structure determination because they are multi-structured yet not disordered, and the resulting conformational ensembles are essential for understanding function. Determining such ensembles is difficult because many measurements that capture multiple conformational populations provide sparse data. A powerful opportunity exists to leverage molecular simulations for spectroscopic experiment selection. We have developed an information-theoretic approach to guide experiments by identifying which measurements best refine the underlying conformational ensemble. We have tested this approach on three flexible bacterial proteins. For proteins where a clear mechanistic hypothesis drives label selection, our approach systematically identifies labels that would test this hypothesis. Furthermore, when available data do not yield an obvious mechanistically-guided label selection strategy, our approach guides label selection and produces conformational refinement that significantly outperforms standard structure-guided approaches. Our information-theoretic approach to label selection thus offers a particular advantage when refining challenging, underdetermined protein conformational ensembles.

bioinformatics↗

bioRxiv2017

Extremely rare variants reveal patterns of germline mutation rate heterogeneity in humans

A detailed understanding of the genome-wide variability of single-nucleotide germline mutation rates is essential to studying human genome evolution. Here we use [~]36 million singleton variants from 3,560 whole-genome sequences to infer fine-scale patterns of mutation rate heterogeneity. Mutability is jointly affected by adjacent nucleotide context and diverse genomic features of the surrounding region, including histone modifications, replication timing, and recombination rate, sometimes suggesting specific mutagenic mechanisms. Remarkably, GC content, DNase hypersensitivity, CpG islands, and H3K36 trimethylation are associated with both increased and decreased mutation rates depending on nucleotide context. We validate these estimated effects in an independent dataset of [~]46,000 de novo mutations, and confirm our estimates are more accurate than previously published estimates based on ancestrally older variants without considering genomic features. Our results thus provide the most refined portrait to date of the factors contributing to genome-wide variability of the human germline mutation rate.

genomics↗

bioRxiv2016

INFERENCE OF CELL TYPE COMPOSITION FROM HUMAN BRAIN TRANSCRIPTOMIC DATASETS ILLUMINATES THE EFFECTS OF AGE, MANNER OF DEATH, DISSECTION, AND PSYCHIATRIC DIAGNOSIS

Psychiatric illness is unlikely to arise from pathology occurring uniformly across all cell types in affected brain regions. Despite this, transcriptomic analyses of the human brain have typically been conducted using macro-dissected tissue due to the difficulty of performing single-cell type analyses with donated post-mortem brains. To address this issue statistically, we compiled a database of several thousand transcripts that were specifically-enriched in one of 10 primary cortical cell types in previous publications. Using this database, we predicted the relative cell type composition for 833 human cortical samples using microarray or RNA-Seq data from the Pritzker Consortium (GSE92538) or publicly-available databases (GSE53987, GSE21935, GSE21138, CommonMind Consortium). These predictions were generated by averaging normalized expression levels across transcripts specific to each cell type using our R-package BrainInABlender (validated and publicly-released: https://github.com/hagenaue/BrainInABlender). Using this method, we found that the principal components of variation in the datasets strongly correlated with the neuron to glia ratio of the samples.\n\nThis variability was not simply due to dissection - the relative balance of brain cell types appeared to be influenced by a variety of demographic, pre- and post-mortem variables. Prolonged hypoxia around the time of death predicted increased astrocytic and endothelial gene expression, illustrating vascular upregulation. Aging was associated with decreased neuronal gene expression. Red blood cell gene expression was reduced in individuals who died following systemic blood loss. Subjects with Major Depressive Disorder had decreased astrocytic gene expression, mirroring previous morphometric observations. Subjects with Schizophrenia had reduced red blood cell gene expression, resembling the hypofrontality detected in fMRI experiments. Finally, in datasets containing samples with especially variable cell content, we found that controlling for predicted sample cell content while evaluating differential expression improved the detection of previously-identified psychiatric effects. We conclude that accounting for cell type can greatly improve the interpretability of transcriptomic data.

bioinformatics↗

bioRxiv2016

A sensitized mutagenesis screen in Factor V Leiden mice identifies novel thrombosis suppressor loci

Factor V Leiden (F5L) is a common genetic risk factor for venous thromboembolism in humans. We conducted a sensitized ENU mutagenesis screen for dominant thrombosuppressor genes based on perinatal lethal thrombosis in mice homozygous for F5L (F5L/L) and haploinsufficient for tissue factor pathway inhibitor (Tfpi+/-). F8 deficiency enhanced survival of F5L/L Tfpi+/- mice, demonstrating that F5L/L Tfpi+/- lethality is genetically suppressible. ENU-mutagenized F5L/L males and F5L/+ Tfpi+/- females were crossed to generate 6,729 progeny, with 98 F5L/L Tfpi+/- offspring surviving until weaning. Sixteen lines exhibited transmission of a putative thrombosuppressor to subsequent generations, with these lines referred to as MF5L (Modifier of Factor 5 Leiden) 1-16. Linkage analysis in MF5L6 identified a chromosome 3 locus containing the tissue factor gene (F3). Though no ENU-induced F3 mutation was identified, haploinsufficiency for F3 (F3+/-) suppressed F5L/L Tfpi+/- lethality. Whole exome sequencing in MF5L12 identified an Actr2 gene point mutation (p.R258G) as the sole candidate. Inheritance of this variant is associated with suppression of F5L/L Tfpi+/- lethality (p=1.7x10-6), suggesting that Actr2p.R258G is thrombosuppressive. CRISPR/Cas9 experiments to generate an independent Actr2 knockin/knockout demonstrated that Actr2 haploinsufficiency is lethal, supporting a hypomorphic or gain of function mechanism of action for Actr2p.R258G. Our findings identify F8 and the Tfpi/F3 axis as key regulators in determining thrombosis balance in the setting of F5L and also suggest a novel role for Actr2 in this process.\n\nSignificance StatementVenous thromboembolism (VTE) is a common disease characterized by the formation of inappropriate blood clots. Inheritance of specific genetic variants, such as the Factor V Leiden polymorphism, increases VTE susceptibility. However, only ~10% of people inheriting Factor V Leiden develop VTE, suggesting the involvement of other genes that are currently unknown. By inducing random genetic mutations into mice with a genetic predisposition to VTE, we identified two genomic regions that reduce VTE susceptibility. The first includes the gene for blood coagulation Factor 3 and its role was confirmed by analyzing mice with an independent mutation in this gene. The second contains a mutation in the Actr2 gene. These findings identify critical genes for the regulation of blood clotting risk.

genetics↗