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Biology subjects

Di, L.

Publications and source records attributed to Di, L..

14 recordsLinked to original sources

Exploring the Biological Mechanisms of Severe COVID-19 in the Elderly: Insights from an Aged Mouse Model

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in a global health crisis, particularly affecting the elderly, who are more susceptible to severe outcomes. However, definitive parameters or mechanisms underlying the severity of COVID-19 in elderly people remain confused. Thus, this study seeks to elucidate the mechanism behind the increased vulnerability of elderly individuals to severe COVID-19. We employed an aged mouse model with a mouse-adapted SARS-CoV-2 strain to mimic the severe symptoms observed in elderly patients with COVID-19. Comprehensive analyses of the whole lung were performed using transcriptome and proteome sequencing, comparing data from aged and young mice. For transcriptome analysis, bulk RNA sequencing was conducted using an Illumina sequencing platform. Proteomic analysis was performed using mass spectrometry following protein extraction, digestion, and peptide labeling. We analyzed the transcriptome and proteome profiles of young and aged mice and discovered that aged mice exhibited elevated baseline levels of inflammation and tissue damage repair. After SARS-CoV-2 infection, aged mice showed increased antiviral and inflammatory responses; however, these responses were weaker than those in young mice, with significant complement and coagulation cascade responses. In summary, our study demonstrates that the increased vulnerability of the elderly to severe COVID-19 can be attributed to an attenuated antiviral response and the overactivation of complement and coagulation cascades.

immunology↗

A Fuzzy sequencer for rapid DNA fragment counting and genotyping

High-throughput sequencing technologies generate a vast number of DNA sequence reads simultaneously, which are subsequently analyzed using the information contained within these fragmented reads. The assessment of sequencing technology relies on information efficiency, which measures the amount of information entropy produced per sequencing reaction cycle. In this study, we propose a fuzzy sequencing strategy that exhibits information efficiency more than twice of currently prevailing cyclic reversible terminator sequencing methods. To validate our approach, we developed a fully functional and high-throughput fuzzy sequencer. This sequencer implements a highly efficient fluorogenic sequencing-by-synthesis chemistry and underwent testing across various application scenarios, including copy-number variation detection, noninvasive prenatal testing, transcriptome profiling, mutation genotyping, and metagenomic profling. Our findings unequivocally demonstrate that the fuzzy sequencing strategy outperforms existing methods in terms of information efficiency and delivers accurate resequencing results with faster turnaround times. One Sentence SummaryA fuzzy sequencer can exceed current limit of information efficiency of DNA sequencers for resequencing applications.

genomics↗

Development of recombinant monoclonal antibodies targeting conserved VlsE epitopes in Lyme disease pathogens

VlsE (variable major protein-like sequence, expressed) is an outer surface protein of the Lyme disease pathogen (Borreliella species) and a key diagnostic biomarker of Lyme disease. However, the high sequence variability of VlsE poses a challenge to the development of consistent VlsE-based diagnostics and therapeutics. In addition, the standard diagnostic protocols detect immunoglobins elicited by the Lyme pathogen, not the presence of pathogen or its derived antigens. Here we describe the development of recombinant monoclonal antibodies (rMAbs) that bind specifically to conserved epitopes on VlsE. We first quantified amino-acid sequence variability encoded by the vls genes from thirteen B. burgdorferi genomes by evolutionary analyses. We showed broad inconsistencies of the sequence phylogeny with the genome phylogeny, indicating rapid gene duplications, losses, and recombination at the vls locus. To identify conserved epitopes, we synthesized peptides representing five long conserved invariant regions (IRs) on VlsE. We tested the antigenicity of these five IR peptides using sera from three mammalian host species including human patients, the natural reservoir white-footed mouse (Peromyscus leucopus), and VlsE-immunized New Zealand rabbits (Oryctolagus cuniculus). The IR4 and IR6 peptides emerged as the most antigenic and reacted strongly with both the human and rabbit sera, while all IR peptides reacted poorly with sera from natural hosts. Four rMAbs binding specifically to the IR4 and IR6 peptides were identified, cloned, and purified. Given their specific recognition of the conserved epitopes on VlsE, these IR-specific rMAbs are promising diagnostic and theragnostic agents for direct detection of Lyme disease pathogens regardless of strain heterogeneity.

microbiology↗

SHERRY2: A method for rapid and sensitive single cell RNA-seq

Prevalent single cell transcriptomic profiling (scRNA-seq) mechods are mainly based on synthesis and enrichment of full-length double-stranded complementary DNA. These approaches are challenging to generate accurate quantification of transcripts when their abundance is low or their full-length amplifications are difficult. Based on our previous finding that Tn5 transposase can directly cut-and-tag DNA/RNA hetero-duplexes, we present SHERRY2, a specifically optimized protocol for scRNA-seq without second strand cDNA synthesis. SHERRY2 is free of pre-amplification and eliminates the sequence-dependent bias. In comparison with other widely-used scRNA-seq methods, SHERRY2 exhibits significantly higher sensitivity and accuracy even for single nuclei. Besides, SHERRY2 is simple and robust, and can be easily scaled up to high-throughput experiments. When testing single lymphocytes and neuron nuclei, SHERRY2 not only obtained accurate countings of transcription factors and long non-coding RNAs, but also provided bias-free results that enriched genes in specific cellular components or functions, which outperformed other protocols. With a few thousand cells sequenced by SHERRY2, we confirmed expression and dynamics of Myc in different cell types of germinal centers, which were previously only revealed by gene-specific amplification methods. SHERRY2 is able to provide high sensitivity, high accuracy, and high throughput for those applications that require high number of genes identified in each cell. It can reveal the subtle transcriptomic difference between cells and facilitate important biological discoveries.

genomics↗

Low frequency somatic copy number alterations in normal human lymphocytes revealed by large scale single-cell whole genome profiling

Genomic-scale somatic copy number alterations in healthy humans are difficult to investigate because of low occurrence rates and the structural variations stochastic natures. Using a Tn5-transposase assisted single-cell whole genome sequencing method, we sequenced over 20,000 single lymphocytes from 16 individuals. Then, with the scale increased to a few thousand single cells per individual, we found that about 7.5% of the cells had large-size copy number alterations. Trisomy 21 was the most prevalent aneuploid event among all autosomal copy number alterations, while monosomy X occurred most frequently in over-30-year-old females. In the monosomy X single cells from individuals with phased genomes and identified X-inactivation ratios in bulk, the inactive X Chromosomes were lost more often than were the active ones.

genomics↗

Following the Trail of One Million Genomes: Footprints of SARS-CoV-2 Adaptation to Humans

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has accumulated genomic mutations at an approximately linear rate since it first infected human populations in late 2019. Controversies remain regarding the identity, proportion, and effects of adaptive mutations as SARS-CoV-2 evolves from a bat-to a human-adapted virus. The potential for vaccine-escape mutations poses additional challenges in pandemic control. Despite being of great interest to therapeutic and vaccine development, human-adaptive mutations in SARS-CoV-2 are masked by a genome-wide linkage disequilibrium under which neutral and even deleterious mutations can reach fixation by chance or through hitchhiking. Furthermore, genome-wide linkage equilibrium imposes clonal interference by which multiple adaptive mutations compete against one another. Informed by insights from microbial experimental evolution, we analyzed close to one million SARS-CoV-2 genomes sequenced during the first year of the COVID-19 pandemic and identified putative human-adaptive mutations according to the rates of synonymous and missense mutations, temporal linkage, and mutation recurrence. Furthermore, we developed a forward-evolution simulator with the realistic SARS-CoV-2 genome structure and base substitution probabilities able to predict viral genome diversity under neutral, background selection, and adaptive evolutionary models. We conclude that adaptive mutations have emerged early, rapidly, and constantly to dominate SARS-CoV-2 populations despite clonal interference and purifying selection. Our analysis underscores a need for genomic surveillance of mutation trajectories at the local level for early detection of adaptive and immune-escape variants. Putative human-adaptive mutations are over-represented in viral proteins interfering host immunity and binding host-cell receptors and thus may serve as priority targets for designing therapeutics and vaccines against human-adapted forms of SARS-CoV-2.

evolutionary biology↗

Maximum Antigen Diversification in a Lyme Bacterial Population and Evolutionary Strategies to Overcome Pathogen Diversity

Natural populations of microbes and their hosts are engaged in an arms race in which microbes diversify to escape host immunity while hosts evolve novel immunity. This co-evolutionary process, known as the "Red Queen" hypothesis, poses a fundamental challenge to the development of broadly effective vaccines and diagnostics against a diversifying pathogen. Based on surveys of natural allele frequencies and experimental immunization of mice, we show minimal antigenic cross-reactivity among natural variants of the outer surface protein C (OspC), a dominant antigen of a Lyme Disease-causing bacterium (Borrelia burgdorferi). To overcome the challenge of OspC antigenic diversity to clinical development of preventive measures, we implemented a number of evolution-based strategies to broaden OspC immunological cross-reactivity. In particular, the centroid algorithm - a genetic algorithm to minimize sequence differences with natural variants - generated synthetic OspC analogs with the greatest promise as diagnostic and vaccine candidates against diverse Lyme pathogen strains coexisting in the Northeast United States. Mechanistically, we propose a model of runaway maximum antigen di-versification (MAD) mediated by amino-acid variations distributed across hypervariable regions on the OspC molecule. Under the MAD model, evolutionary centroids display high cross-reactivity by occupying the central void in the antigenic space excavated by diversifying natural variants. In contrast to the vaccine design based on concatenated epitopes, the centroid algorithm generates analogs of native antigens and is automated. The MAD model and evolution-inspired antigen designs have broad implications for combating diversifying pathogens driven by pathogen-host coevolution. ImportanceMicrobial pathogens rely on molecular diversity of cell surface antigens to escape host immunity. Vaccines based on one antigen variant often fail to protect the host against pathogens carrying other variants. Here we show evolution-based designs of synthetic antigens that are broadly reactive to all natural variants. The evolutionary analogs of a major surface antigen of a Lyme disease bacterium (Borrelia burgdorferi) showed promise as vaccine candidates against diverse pathogen strains coexisting in the endemic areas of Lyme disease in Northeast United States. Our evolution-based computational design is automated, generates molecular analogs of natural antigens, and opens a novel path to combating fast-evolving microbial pathogens.

microbiology↗

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↗

Default Mode Network Ventral Hub Connectivity Associated with Memory Impairment in Temporal Lobe Epilepsy Surgery

In patients undergoing surgery for intractable temporal lobe epilepsy, the relationship between the default mode network and patients neurocognitive outcome remains unclear. The objective of this study is to employ non-invasive network mapping to identify the relationship between subdivisions of the default mode network and neurocognitive function before and after epilepsy surgery in patients with temporal lobe epilepsy. Twenty-seven medically patients with medically refractory temporal lobe epilepsy were prospectively enrolled and received resting state functional MRI and neuropsychological testing both pre- and post-operatively. Connectivity within the default mode network was modeled and average connectivity within the networks was calculated. Higher pre-operative connectivity in the ventral default mode network hub correlated with impaired baseline performance in a visual memory task. Post-operatively, a decrease in ventral but not dorsal default mode network connectivity was correlated with a deterioration of verbal and logical memory after surgery. Overall, higher connectivity in the ventral default mode network hub was associated with poor memory function in patients with temporal lobe epilepsy both before and after temporal lobe surgery. Pre-operatively, higher ventral connectivity was associated with worse visual function. Post-operatively, decreased connectivity of the ventral and dorsal default mode network was correlated with a greater decrease in logical and verbal memory when compared with the pre-operation baseline. An imbalance in default mode network connectivity towards the ventral stream and more widespread epilepsy networks may be used to predict memory impairments following surgical intervention and may lead to more tailored surgical decision making based on this non-invasive network modeling.

neuroscience↗

An Engineered Genetic Circuit for Lactose Intolerance Alleviation Coupled with Gut Microbiota Recovery

BackgroundLactose malabsorption occurs in around 68% of the world populations, causing lactose intolerance (LI) symptoms such as abdominal pain, bloating and diarrhoea. To alleviate LI, previous studies mainly focused on strengthening intestinal {beta}-galactosidase activity but neglected the inconspicuous colon pH drop caused by gut microbes fermentation on non-hydrolysed lactose. The colon pH drop will reduce intestinal {beta}-galactosidase activity and influence the intestinal homeostasis. ResultsHere, we synthesized a tri-stable-switch circuit equipped with high {beta}-galactosidase activity and pH rescue ability. This circuit can switch in functionality between expression of {beta}-galactosidase and expression of l-lactate dehydrogenase in respond to intestinal lactose signal and intestinal pH signal. We confirmed the circuit functionality was efficient using 12-hrs in vitro culture at a range of pH levels, as well as 6-hrs in vivo simulations in mice colon. Moreover, another 21-days mice trial indicated that this circuit can recover lactose-effected gut microbiota of mice to the status (enterotypes) similar to that of mice without lactose intake. ConclusionsTaken together, the tri-stable-switch circuit can serve as a promising prototype for LI symptoms relief, especially by flexibly adapting to environmental variation, stabilizing colon pH and restoring gut microbiota.

bioengineering↗

MINERVA: A facile strategy for SARS-CoV-2 whole genome deep sequencing of clinical samples

The novel coronavirus disease 2019 (COVID-19) pandemic poses a serious public health risk. Analyzing the genome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from clinical samples is crucial for the understanding of viral spread and viral evolution, as well as for vaccine development. Existing sample preparation methods for viral genome sequencing are demanding on user technique and time, and thus not ideal for time-sensitive clinical samples; these methods are also not optimized for high performance on viral genomes. We have developed MetagenomIc RNA EnRichment VirAl sequencing (MINERVA), a facile, practical, and robust approach for metagenomic and deep viral sequencing from clinical samples. This approach uses direct tagmentation of RNA/DNA hybrids using Tn5 transposase to greatly simplify the sequencing library construction process, while subsequent targeted enrichment can generate viral genomes with high sensitivity, coverage, and depth. We demonstrate the utility of MINERVA on pharyngeal, sputum and stool samples collected from COVID-19 patients, successfully obtaining both whole metatranscriptomes and complete high-depth high-coverage SARS-CoV-2 genomes from these clinical samples, with high yield and robustness. MINERVA is compatible with clinical nucleic extracts containing carrier RNA. With a shortened hands-on time from sample to virus-enriched sequencing-ready library, this rapid, versatile, and clinic-friendly approach will facilitate monitoring of viral genetic variations during outbreaks, both current and future.

molecular biology↗

CoV Genome Tracker: tracing genomic footprints of Covid-19 pandemic

SummaryGenome sequences constitute the primary evidence on the origin and spread of the 2019-2020 Covid-19 pandemic. Rapid comparative analysis of coronavirus SARS-CoV-2 genomes is critical for disease control, outbreak forecasting, and developing clinical interventions. CoV Genome Tracker is a web portal dedicated to trace Covid-19 outbreaks in real time using a haplotype network, an accurate and scalable representation of genomic changes in a rapidly evolving population. We resolve the direction of mutations by using a bat-associated genome as outgroup. At a broader evolutionary time scale, a companion browser provides gene-by-gene and codon-by-codon evolutionary rates to facilitate the search for molecular targets of clinical interventions. Availability and ImplementationCoV Genome Tracker is publicly available at http://cov.genometracker.org and updated weekly with the data downloaded from GISAID (http://gisaid.org). The website is implemented with a custom JavaScript script based on jQuery (https://jquery.com) and D3-force (https://github.com/d3/d3-force). Contactweigang@genectr.hunter.cuny.edu, City University of New York, Hunter College Supplementary InformationAll supporting scripts developed in JavaScript, Python, BASH, and PERL programming languages are available as Open Source at the GitHub repository https://github.com/weigangq/cov-browser.

evolutionary biology↗

RNA Sequencing by Direct Tagmentation of RNA/DNA Hybrids

Transcriptome profiling by RNA sequencing (RNA-seq) has been widely used to characterize cellular status but it relies on second strand cDNA synthesis to generate initial material for library preparation. Here we use bacterial transposase Tn5, which has been increasingly used in various high-throughput DNA analyses, to construct RNA-seq libraries without second strand synthesis. We show that Tn5 transposome can randomly bind RNA/DNA heteroduplexes and add sequencing adapters onto RNA directly after reverse transcription. This method, Sequencing HEteRo RNA-DNA-hYbrid (SHERRY), is versatile and scalable. SHERRY accepts a wide range of starting materials, from bulk RNA to single cells. SHERRY offers a greatly simplified protocol, and produces results with higher reproducibility and GC uniformity compared with prevailing RNA-seq methods. Significance StatementRNA sequencing is widely used to measure gene expression in biomedical research; therefore, improvements in the simplicity and accuracy of the technology are desirable. All existing RNA sequencing methods rely on the conversion of RNA into double-stranded DNA through reverse transcription followed by second strand synthesis. The latter step requires additional enzymes and purification, and introduces sequence-dependent bias. Here, we show that Tn5 transposase, which randomly binds and cuts double-stranded DNA, can directly fragment and prime the RNA/DNA heteroduplexes generated by reverse transcription. The primed fragments are then subject to PCR amplification. This provides a new approach for simple and accurate RNA characterization and quantification.

molecular biology↗

Identification and quantification of Lyme pathogen strains by deep sequencing of outer surface protein C (ospC) amplicons

Mixed infection of a single tick or host by Lyme disease spirochetes is common and a unique challenge for diagnosis, treatment, and surveillance of Lyme disease. Here we describe a novel protocol for differentiating Lyme strains based on deep sequencing of the hypervariable outer-surface protein C locus (ospC). Improving upon the traditional DNA-DNA hybridization method, the next-generation sequencing-based protocol is high-throughput, quantitative, and able to detect new pathogen strains. We applied the method to over one hundred infected Ixodes scapularis ticks collected from New York State, USA in 2015 and 2016. Analysis of strain distributions within individual ticks suggests an overabundance of multiple infections by five or more strains, inhibitory interactions among co-infecting strains, and presence of a new strain closely related to Borreliella bissettiae. A supporting bioinformatics pipeline has been developed. With the newly designed pair of universal ospC primers targeting intergenic sequences conserved among all known Lyme pathogens, the protocol could be used for culture-free identification and quantification of Lyme pathogens in wildlife and clinical specimens across the globe.

microbiology↗