Biology subjects

Liu, H.

Publications and source records attributed to Liu, H..

At least 793 records · Page 44Linked to original sources

bioRxiv2020

Single point mutations can potentially enhance infectivity of SARS-CoV-2 revealed by in silico affinity maturation and SPR assay

The RBD (receptor binding domain) of the SARS-CoV-2 virus S (spike) protein mediates the viral cell attachment and serves as a promising target for therapeutics development. Mutations on the S-RBD may alter its affinity to cell receptor and affect the potency of vaccines and antibodies. Here we used an in-silico approach to predict how mutations on RBD affect its binding affinity to hACE2 (human angiotensin-converting enzyme2). The effect of all single point mutations on the interface was predicted. SPR assay result shows that 6 out of 9 selected mutations can strengthen binding affinity. Our prediction has reasonable agreement with the previous deep mutational scan results and recently reported mutants. Our work demonstrated in silico method as a powerful tool to forecast more powerful virus mutants, which will significantly benefit for the development of broadly neutralizing vaccine and antibody.

bioinformatics↗

bioRxiv2020

Extensive High-Order Complexes within SARS-CoV-2 Proteome Revealed by Compartmentalization-Aided Interaction Screening

Bearing the largest single-stranded RNA genome in nature, SARS-CoV-2 utilizes sophisticated replication/transcription complexes (RTCs), mainly composed of a network of nonstructural proteins and nucleocapsid protein, to establish efficient infection. Here, we developed an innovative interaction screening strategy based on phase separation in cellulo, namely compartmentalization of protein-protein interactions in cells (CoPIC). Utilizing CoPIC screening, we mapped the interaction network among RTC-related viral proteins. We identified a total of 47 binary interactions among 14 proteins governing replication, discontinuous transcription, and translation of coronaviruses. Further exploration via CoPIC led to the discovery of extensive ternary complexes composed of these components, which infer potential higher-order complexes. Taken together, our results present an efficient, and robust interaction screening strategy, and indicate the existence of a complex interaction network among RTC-related factors, thus opening up new opportunities to understand SARS-CoV-2 biology and develop therapeutic interventions for COVID-19.

microbiology↗

bioRxiv2020

Determining Aspergillus fumigatus transcription factor expression and function during invasion of the mammalian lung

To gain a better understanding of the transcriptional response of Aspergillus fumigatus during invasive pulmonary infection, we used a NanoString nCounter to assess the transcript levels of 467 A. fumigatus genes during growth in the lungs of immunosuppressed mice. These genes included ones known to respond to diverse environmental conditions and those encoding most transcription factors in the A. fumigatus genome. We found that invasive growth in vivo induces a unique transcriptional profile as the organism responds to nutrient limitation and attack by host phagocytes. This in vivo transcriptional response is largely mimicked by in vitro growth in Aspergillus minimal medium that is deficient in nitrogen, iron, and/or zinc. From the transcriptional profiling data, we selected 9 transcription factor genes that were either highly expressed or strongly up-regulated during in vivo growth. Deletion mutants were constructed for each of these genes and assessed for virulence in mice. Two transcription factor genes were found to be required for maximal virulence. One was rlmA, which governs the ability of the organism to proliferate in the lung. The other was ace1, which regulates of the expression of multiple secondary metabolite gene clusters and mycotoxin genes independently of laeA. Using deletion and overexpression mutants, we determined that the attenuated virulence of the {Delta}ace1 mutant is due to decreased expression aspf1, which specifies a ribotoxin, but is not mediated by reduced expression of the fumigaclavine gene cluster or the fumagillin-pseruotin supercluster. Thus, in vivo transcriptional profiling focused on transcription factors genes provides a facile approach to identifying novel virulence regulators. Author summaryAlthough A. fumigatus causes the majority of cases of invasive aspergillosis, the function of most of the genes in its genome remains unknown. To identify genes encoding transcription factors that may be important for virulence, we used a NanoString nCounter to measure the mRNA levels of A. fumigatus transcription factor genes in the lungs of mice with invasive aspergillosis. The transcriptional profiling data indicate that the organism is exposed to nutrient limitation and stress during growth in the lungs, and that it responds by up-regulating genes that encode mycotoxins and secondary metabolites. In vitro, this response was most closely mimicked by growth in medium that was deficient in nitrogen, iron and/or zinc. Using the transcriptional profiling data, we identified two transcription factors that govern A. fumigatus virulence. These were RlmA, which is governs proliferation in the lung and Ace1, which controls the production of mycotoxins and secondary metabolites.

microbiology↗

bioRxiv2020

Identification of Celastrol as a novel HIV-1 Latency Reversal Agent by an Image-Based Screen

Although current antiretroviral therapies (ART) are successful in controlling HIV-1 infection, a stable viral reservoir reactivates when ART is discontinued. Consequently, there is a major research effort to develop approaches to disrupt the latent viral reservoir and enhance the immune systems ability to clear HIV-1. A number of small molecules, termed latency reversal agents (LRAs), have been identified which can reactivate latent HIV-1 in cell lines and patients cells ex vivo. However, clinical trials have suggested that combinations of LRAs will be required to efficiently reactivate HIV-1 in vivo, especially LRAs that act synergistically by functioning through distinct pathways. To identify novel LRAs, we used an image-based assay to screen a natural compound library for the ability to induce a low level of aggregation of resting primary CD4+ T cells from healthy donors. We identified celastrol as a novel LRA. Celastrol functions synergistically with other classes of LRA to reactivate latent HIV-1 in a Jurkat cell line, suggesting a novel mechanism in its LRA activity. Additionally, celastrol does not appear to activate resting CD4+ T cells at levels at which it can reactivate latent HIV-1. Celastrol appears to represent a novel class of LRAs and it therefore can serve as a lead compound for LRA development.

microbiology↗

bioRxiv2020

Combinatorial Screen of Dynamic Mechanical Stimuli for Predictive Control of MSC Mechano-Responsiveness

Mechanobiological-based control of mesenchymal stromal cells (MSCs) to aid in the engineering and regeneration of load-bearing tissues requires systematic investigations of specific dynamic mechanical stimulation protocols. Using deformable membrane microdevice arrays paired with combinatorial experimental design and modeling, we systematically probed the individual and integrative effects of mechanical stimulation parameters (strain magnitude (STRAIN), rate at which strain is changed (RATE) and duty period (DUTY)) on myofibrogenesis and matrix production of MSCs in 3D hydrogels. These functions were found to be dominantly influenced by a novel and higher-order interactive effect between STRAIN and DUTY. Empirical models based on our combinatorial cue-response data predicted an optimal loading regime in which STRAIN and DUTY were increased synchronously over time, which was validated to most effectively promote MSC matrix production. These findings inform the design of loading regimes for MSC-based engineered tissues and validate a broadly applicable approach to probe multifactorial regulating effects of microenvironmental and mechanobiological cues.

bioengineering↗

bioRxiv2020

Circulating ACE2-expressing Exosomes Block SARS-CoV-2 Virus Infection as an Innate Antiviral Mechanism

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes the coronavirus disease 2019 (COVID-19) with innate and adaptive immune response triggered in such patients by viral antigens. Both convalescent plasma and engineered high affinity human monoclonal antibodies have shown therapeutic potential to treat COVID-19. Whether additional antiviral soluble factors exist in peripheral blood remain understudied. Herein, we detected circulating exosomes that express the SARS-CoV-2 viral entry receptor angiotensin-converting enzyme 2 (ACE2) in plasma of both healthy donors and convalescent COVID-19 patients. We demonstrated that exosomal ACE2 competes with cellular ACE2 for neutralization of SARS-CoV-2 infection. ACE2-expressing (ACE2+) exosomes blocked the binding of the viral spike (S) protein RBD to ACE2+ cells in a dose dependent manner, which was 400- to 700-fold more potent than that of vesicle-free recombinant human ACE2 extracellular domain protein (rhACE2). As a consequence, exosomal ACE2 prevented SARS-CoV-2 pseudotype virus tethering and infection of human host cells at a 50-150 fold higher efficacy than rhACE2. A similar antiviral activity of exosomal ACE2 was further demonstrated to block wild-type live SARS-CoV-2 infection. Of note, depletion of ACE2+ exosomes from COVID-19 patient plasma impaired the ability to block SARS-CoV-2 RBD binding to host cells. Our data demonstrate that ACE2+ exosomes can serve as a decoy therapeutic and a possible innate antiviral mechanism to block SARS-CoV-2 infection.

immunology↗

bioRxiv2020

Aperture: Accurate detection of structural variations and viral integrations in circulating tumor DNA using an alignment-free algorithm

BackgroundThe identification of structural variations (SV) and viral integrations in circulating tumor DNA (ctDNA) is a key step in precision oncology that may assist clinicians for treatment selection and monitoring. However, it is challenging to accurately detect low frequency SVs or SVs involving complex junctions in ctDNA sequencing data due to the short fragment size of ctDNA. ResultsHere, we describe Aperture, a new fast SV caller that applies a unique strategy of k-mer based searching, breakpoint detection using binary labels and candidates clustering to detect SVs and viral integrations in high sensitivity, especially when junctions span repetitive regions, followed by a barcode-based filter to ensure specificity. We evaluated the performance of Aperture in stimulated, reference and real datasets. Aperture demonstrates superior sensitivity and specificity in all tests, especially for low dilution test, compared with existing methods. In addition, Aperture is able to predict sites of viral integration and identify complex SVs involving novel insertions and repetitive sequences in real patient data. ConclusionsUsing a novel alignment-free algorithm, Aperture achieves sensitive, specific and fast detection of structural variations and viral integrations, which may enhance the diagnostic value of ctDNA in clinical application. The executable file and source code are freely available at https://github.com/liuhc8/Aperture.

bioinformatics↗

bioRxiv2020

FGF2 disruption enhances thermogenesis in brown and beige fat to protect against obesity and hepatic steatosis

Since brown and beige fat expend energy in the form of heat via non-shivering thermogenesis, identifying key regulators of thermogenic functions represents a major goal for development of potential therapeutic avenues for obesity and associated disorders. Here, we identified fibroblast growth factor 2 (FGF2) as a novel thermogenic regulator. FGF2 gene disruption resulted in increased thermogenic capability in both brown and beige fat, which was supported by increased UCP1 expression, enhanced respiratory exchange ratio, and elevated thermogenic potential under cold challenge or {beta}-adrenergic stimulation. Thus, deletion of FGF2 protected mice from high fat-induced obesity and hepatic steatosis. Mechanistically, FGF2 acts in autocrine/paracrine fashions in vitro. Exogenous FGF2 supplementation inhibits both PGC-1 and PPAR{gamma} expression through ERK phosphorylation, thereby limiting PGC-1/PPAR{gamma} interactions, and leading to suppression of UCP1 expression and thermogenic activity in brown and beige adipocytes. These findings suggest a viable potential strategy for use of FGF2-selective inhibitors in treatment of combating obesity and related disorders.

cell biology↗

bioRxiv2020

A body map of somatic mutagenesis in morphologically normal human tissues

Somatic mutations accumulated in normal tissues are associated with aging and disease. Here, we performed a comprehensive genomic analysis of 1,737 morphologically normal tissue biopsies (~ 600 cells each), mostly from the epithelia, of nine organs from five donors. We found that somatic mutation accumulations and clonal expansions are widespread, although with variable extent, in morphologically normal human tissues. Somatic copy number alterations were rarely detected, except for tissues from esophagus and cardia. Endogenous mutational processes like SBS1 and SBS5 are ubiquitous among normal tissues though exhibiting different relative activities. Exogenous mutational processes like SBS22 were found in different tissues from the same donor. We reconstructed the spatial somatic clonal architecture with sub-millimeter resolution. In epithelial tissues from esophagus and cardia, macroscopic somatic clones expanded to several millimeters were frequently seen, whereas in tissues from colon, rectum, and duodenum somatic clones were microscopic in size and evolved independently. Our study depicted a body map of somatic mutations and clonal expansions from the same individuals, and it revealed that the degree of somatic clonal expansion and enrichment of driver mutations are highly organ specific.

genomics↗

bioRxiv2020

Topoisomerase 1 inhibition therapy protects against SARS-CoV-2-induced inflammation and death in animal models.

The ongoing pandemic caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is currently affecting millions of lives worldwide. Large retrospective studies indicate that an elevated level of inflammatory cytokines and pro-inflammatory factors are associated with both increased disease severity and mortality. Here, using multidimensional epigenetic, transcriptional, in vitro and in vivo analyses, we report that Topoisomerase 1 (Top1) inhibition suppresses lethal inflammation induced by SARS-CoV-2. Therapeutic treatment with two doses of Topotecan (TPT), a FDA-approved Top1 inhibitor, suppresses infection-induced inflammation in hamsters. TPT treatment as late as four days post-infection reduces morbidity and rescues mortality in a transgenic mouse model. These results support the potential of Top1 inhibition as an effective host-directed therapy against severe SARS-CoV-2 infection. TPT and its derivatives are inexpensive clinical-grade inhibitors available in most countries. Clinical trials are needed to evaluate the efficacy of repurposing Top1 inhibitors for COVID-19 in humans.

microbiology↗

bioRxiv2020

Regulating enzymatic reactions in Escherichia coli utilizing light-responsive cellular compartments based on liquid-liquid phase separation

Enzymatic reactions in cells are well organized into different compartments, among which protein-based membraneless compartments formed through liquid-liquid phase separation (LLPS) are believed to play important roles1,2. Hijacking them for our own purpose has promising applications in metabolic engineering3. Yet, it is still hard to precisely and dynamically control target enzymatic reactions in those compartments4. To address those problems, we developed Photo-Activated Switch in E. coli (PhASE), based on phase separating scaffold proteins and optogenetic tools. In this system, a protein of interest (POI) can be enriched up to 15-fold by LLPS-based compartments from cytosol within only a few seconds once activated by light, and become fully dispersed again within 15 minutes. Furthermore, we explored the potentiality of the LLPS-based compartment in enriching small organic molecules directly via chemical-scaffold interaction. With enzymes and substrates co-localized under light induction, the overall reaction efficiency could be enhanced. Using luciferin and catechol oxidation as model enzymatic reactions, we found that they could accelerate 2.3-fold and 1.6-fold, respectively, when regulated by PhASE. We anticipate our system to be an extension of the synthetic biology toolkit, facilitating rapid recruitment and release of POIs, and reversible regulation of enzymatic reactions.

synthetic biology↗

bioRxiv2020

SCReadCounts: Estimation of cell-level SNVs from scRNA-seq data

Recent studies have demonstrated the utility of scRNA-seq SNVs to distinguish tumor from normal cells, characterize intra-tumoral heterogeneity, and define mutation-associated expression signatures. In addition to cancer studies, SNVs from single cells have been useful in studies of transcriptional burst kinetics, allelic expression, chromosome X inactivation, ploidy estimations, and haplotype inference. To aid these types of studies, we have developed a tool, SCReadCounts, for cell-level tabulation of the sequencing read counts bearing SNV reference and variant alleles from barcoded scRNA-seq alignments. Provided genomic loci and expected alleles, SCReadCounts generates cell-SNV matrices with the absolute variant- and reference-harboring read counts, as well as cell-SNV matrices of expressed Variant Allele Fraction (VAFRNA) suitable for a variety of downstream applications. We demonstrate three different SCReadCounts applications on 59,884 cells from seven neuroblastoma samples: (1) estimation of cell-level expression of known somatic mutations and RNA-editing sites, (2) estimation of celllevel allele expression of germline heterozygous SNVs, and (3) a discovery mode assessment of the reference and each of the three alternative nucleotides at genomic positions of interest that does not require prior SNV information. For the later, we applied SCReadCounts on the coding regions of KRAS, where it identified known and novel recurrent somatic mutations in a low-to-moderate proportion of cells. The SCReadCounts read counts module is benchmarked against the analogous modules of GATK and Samtools. SCReadCounts is freely available (https://github.com/HorvathLab/NGS) as 64-bit self-contained binary distributions for Linux and MacOS, in addition to Python source.

bioinformatics↗

bioRxiv2020

Deletion of Letmd1 leads to the disruption of mitochondrial function in brown adipose tissue

Human cervical cancer oncogene (HCCR-1), also named as LETMD1, is a LETM-domain containing outer mitochondrial membrane protein which plays an important role in the carcinogenesis of cancers. Surprisingly, we found that loss of Letmd1 in mice leads to multiply severe abnormities, such as the brown adipose tissue (BAT) whitening, disruption of thermogenesis, cold-induced death, diet-induced obesity, hyperglycinemia and insulin resistance. Mechanistically, deletion of Letmd1 in BAT causes the reduction of mitochondrial calcium ion, which in turn results in the suppressed fission of mitochondria, and ultimately leads to the depletion of Ucp1-mediated BAT heat production. This study indicates that LETMD1 plays a crucial role in controlling BAT thermogenesis and energy homeostasis by regulating mitochondrial structures and functions, and also provides a novel insight for the clinical biomarker and therapeutical target of oncogene for the metabolic disorders. HighlightsO_LILetmd1 is an oncogene and also highly expressed in brown adipose tissue (BAT) of human and mice. C_LIO_LILoss of Letmd1 leads to BAT whitening, diet-induced obesity, hyperglycemia and insulin resistant. C_LIO_LILetmd1 knockout causes the disruption of thermogenesis and death at 4{degrees}C exposure. C_LIO_LIDeletion of Letmd1 results in mitochondrial calcium homeostasis disorders. C_LI Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=159 HEIGHT=200 SRC="FIGDIR/small/388199v2_ufig1.gif" ALT="Figure 1"> View larger version (65K): org.highwire.dtl.DTLVardef@bee6adorg.highwire.dtl.DTLVardef@11a7cc1org.highwire.dtl.DTLVardef@1f4699forg.highwire.dtl.DTLVardef@142699a_HPS_FORMAT_FIGEXP M_FIG C_FIG

physiology↗

bioRxiv2020

Genome-wide screen of genomic imprinting in endosperm and population-level analysis reveal allelic variation for imprinting in flax

Genomic imprinting is an epigenetic phenomenon caused by the biased expression of maternally and paternally inherited alleles. In flowering plants, genomic imprinting predominantly occurs in triploid endosperm and plays a vital role in seed development. In this study, we identified 241 candidate imprinted genes including 143 maternally expressed imprinted genes (MEGs) and 98 paternally expressed imprinted genes (PEGs) in flax (Linum usitatissimum L.) endosperm using deep RNA sequencing. The conservation of imprinting in plants is very limited and imprinting clustering is not a general feature. MEGs tends to be endosperm expression specific, while PEGs are non-tissue specific. Imprinted SNPs differentiated 200 flax cultivars into oil flax, oil-fiber dual purpose flax (OF) and fiber flax subgroups, suggesting that genomic imprinting contributes to intraspecific variation in flax. The nucleotide diversity ({pi}) of imprinted genes in oil flax subgroup is significantly higher than that in fiber flax subgroup, indicating that some imprinted genes undergo positive selection during flax domestication from oil flax to fiber flax. Imprinted genes undergo positive selection is related to the functions. Eleven imprinted genes related to seed size and weight were identified using the candidate gene-based association study. Our study provides information for further exploring the function and genomic variation of imprinted genes in flax population.

plant biology↗

bioRxiv2020

HTT silencing delays onset and slows progression of Huntington disease like phenotype: Monitoring with a novel neurovascular biomarker

Huntingtons disease (HD) is a dominantly inherited, fatal neurodegenerative disorder caused by a CAG expansion in the Huntingtin (HTT) gene, coding for pathologic mutant HTT protein (mHTT). Because of its gain-of-function mechanism and monogenic etiology, strategies to lower HTT are being actively investigated as disease-modifying therapies. Most approaches are currently targeted at the manifest HD stage, when clinical outcomes are used to evaluate the effectiveness of therapy. However, as almost 50% of striatal volume has been lost at the time of onset of manifest HD it would be preferable to begin therapy in the premanifest period. An unmet challenge is how to evaluate therapeutic efficacy before the presence of clinical symptoms as outcome measures. To address this, we have been developing more sensitive biomarkers such as functional neuroimaging with the goal of identifying noninvasive biomarkers that provide insight into the best time to introduce HTT-lowering treatment. In this study, we mapped the temporal trajectories of arteriolar cerebral blood volumes (CBVa) using inflow-based vascular-space-occupancy (iVASO) MRI technique in an HD mouse model. Significantly elevated CBVa was evident in premanifest zQ175 HD mice prior to motor deficits and striatal atrophy, recapitulating altered CBVa in human premanifest HD. CRISPR/Cas9-mediated non-allele-specific HTT silencing in striatal neurons restored altered CBVa in premanifest zQ175 mice, delayed onset of striatal atrophy, and slowed the progression of motor phenotype and brain pathology. This study showed the potential of CBVa as a noninvasive fMRI biomarker for premanifest HD clinical trials and demonstrates long-term benefits of introducing an HTT lowering treatment in the premanifest HD.

neuroscience↗

bioRxiv2020

The expression of PDCD1 and CD274 in T cells and macrophages correlated positively with COVID-19 severity

The immune responses underlying the infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remain unclear. To help understand the pathology of coronavirus disease 2019 (COVID-19) pandemics, public data were analyzed and the expression of PDCD1 (encoding PD-1) and CD274 (encoding PD-L1) in T cells and macrophages were identified to correlate positively with COVID-19 severity.

immunology↗

bioRxiv2020

A dominant-negative SOX18 mutant disrupts multiple regulatory layers essential to transcription factor activity.

Few genetically dominant mutations involved in human disease have been fully explained at the molecular level. In cases where the mutant gene encodes a transcription factor, the dominant-negative mode of action of the mutant protein is particularly poorly understood. Here, we studied the genome-wide mechanism underlying a dominant-negative form of the SOX18 transcription factor (SOX18RaOp) responsible for both the classical mouse mutant Ragged opossum and the human genetic disorder Hypotrichosis-Lymphedema-Telangiectasia-Renal Syndrome. Combing three single-molecule imaging assays in living cells, we found that SOX18RaOp disrupts the system through an accumulation of molecular interferences which impair several functional properties of the wild-type SOX18 protein, including its chromatin-binding dynamics. The dominant-negative effect is further amplified by recruiting the interactome of its wild-type counterpart, which perturbs regulatory nodes such as SOX7 and MEF2C. Our findings explain in unprecedented detail the multi-layered process that underpins the molecular etiology of dominant-negative transcription factor function.

cell biology↗

bioRxiv2020

Network-based Virus-Host Interaction Prediction with Application to SARS-CoV-2

COVID-19, caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has quickly become a global health crisis since the first report of infection in December of 2019. However, the infection spectrum of SARS-CoV-2 and its comprehensive protein-level interactions with hosts remain unclear. There is a massive amount of under-utilized data and knowledge about RNA viruses highly relevant to SARS-CoV-2 and their hosts proteins. More in-depth and more comprehensive analyses of that knowledge and data can shed new insight into the molecular mechanisms underlying the COVID-19 pandemic and reveal potential risks. In this work, we constructed a multi-layer virus-host interaction network to incorporate these data and knowledge. A machine learning-based method, termed Infection Mechanism and Spectrum Prediction (IMSP), was developed to predict virus-host interactions at both protein and organism levels. Our approach revealed five potential infection targets of SARS-CoV-2, which deserved public health attention, and eight highly possible interactions between SARS-CoV-2 proteins and human proteins. Given a new virus, IMSP can utilize existing knowledge and data about other highly relevant viruses to predict multi-scale interactions between the new virus and potential hosts.

bioinformatics↗