Biology subjects

Lo, T.

Publications and source records attributed to Lo, T..

10 recordsLinked to original sources

bioRxiv2025

Woodsmoke and Diesel Exhaust: Distinct Transcriptomic Profiles in the Human Airway Epithelium

Climate change is increasing the frequency and severity of wildfires globally, causing significant woodsmoke (WS) emissions. Vehicles emit sizable amounts of toxic traffic-related air pollution (TRAP), for which diesel exhaust (DE) is a model. Both WS and DE contain particulate matter <2.5 microns (PM2.5) which deeply penetrates the lungs, causing respiratory epithelial inflammation that drives health effects. Regulations focus on PM2.5 concentration, despite emerging research that highlights how composition mediates health effects. As WS and DE are compositionally distinct, we conducted the first head-to-head comparison of effects on the transcriptomes of air-liquid interface cultured primary human bronchial epithelial cells (HBEC). Differentiated donor-matched HBEC transwells were exposed for 2-hours to filtered air (FA; control), or WS (furnace tube burning pine) or DE (Hatz 1B30E generator) both diluted to 300 {micro}g/m3 of PM2.5. WS had higher ultrafine PM, whereas DE exposure contained significantly higher NO2, CO, and O3. RNA sequencing showed that WS exposure resulted in 119 ({uparrow}41, {downarrow}78) differentially expressed genes, while DE modulated 399 ({uparrow}255, {downarrow}144) compared to FA exposure. WS was associated with small ribosomal subunit and cytochrome complex related genes, while DE exposure was associated with HIF-1 signaling, respiratory chain complex and interferon alpha/beta signaling/ISG15-protein conjugation, suggesting how TRAP exposure may enhance infection risk. We also analyzed exposure effects on protein immune-mediators. We demonstrate that two major air pollution sources modulate different genes and pathways in HBECs, with minimal overlap. This informs the debate regarding the regulatory focus on concentration and assumptions that similar concentrations of air pollution have indistinct effects. HighlightsO_LILung health effects of diesel exhaust (DE) and wood smoke (WS) are underexplored C_LIO_LIRNAseq of DE and WS-exposed primary lung epithelial cells revealed larger DE effects C_LIO_LIDE showed greater repression of host antiviral response-associated genes than WS C_LIO_LIA regulatory focus on PM concentration may miss composition-specific lung effects C_LI

bioinformatics↗

bioRxiv2022

The high-resolution in vivo measurement of replication fork velocity and pausing

An important step towards understanding the mechanistic basis of the central dogma is the quantitative characterization of the dynamics of nucleic-acid-bound molecular motors in the context of the living cell, where a crowded cytoplasm as well as competing and potentially antagonistic processes may significantly affect their rapidity and reliability. To capture these dynamics, we develop a novel method, lag-time analysis, for measuring in vivo dynamics. The approach uses exponential growth as the stopwatch to resolve dynamics in an asynchronous culture and therefore circumvents the difficulties and potential artifacts associated with synchronization or fluorescent labeling. Although lag-time analysis has the potential to be widely applicable to the quantitative analysis of in vivo dynamics, we focus on an important application: characterizing replication dynamics. To benchmark the approach, we analyze replication dynamics in three different species and a collection of mutants. We provide the first quantitative locus-specific measurements of fork velocity, in units of kb per second, as well as replisome-pause durations, some with the precision of seconds. The measured fork velocity is observed to be both locus and time dependent, even in wild-type cells. In addition to quantitatively characterizing known phenomena, we detect brief, locus-specific pauses at rDNA in wild-type cells for the first time. We also observe temporal fork velocity oscillations in three highly-divergent bacterial species. Lag-time analysis not only has great potential to offer new insights into replication, as demonstrated in the paper, but also has potential to provide quantitative insights into other important processes.

biophysics↗

bioRxiv2022

Sleeve gastrectomy promotes colitis-associated colorectal cancer in a murine model via a modified gut microbiome

Colorectal cancer (CRC) remains the third leading cause of cancer death in the United States with an alarming rise among young (<50-years-old) patients.1 Epidemiologically, obesity appears to be a risk factor for CRC.1 Although bariatric surgery has been shown to be associated with decreased risk for most cancers, studies to date on bariatric surgery and CRC continue to yield conflicting results.2 One possible explanation for this seeming irreconcilability is the inherent heterogeneity of CRC with its varied mechanisms. This is likely compounded by the differing bariatric operations currently employed. Here, we sharpen our focus and investigate how the most performed bariatric operation, sleeve gastrectomy (SG), affects colitis-associated CRC. Using a murine model, we found that SG significantly exacerbates both colitis and colitis-associated CRC. Using a germ-free (GF) microbiota transplant model, we found that the post-SG microbiota, when transplanted into GF mice, is capable of independently recapitulating the tumor-promoting phenotype of SG. Our results suggest that the postsurgical microbiome plays a key causal role in the increased risk for CRC after SG. This finding represents the first step in our understanding of this complex relationship that is at the intersection of two rising public health threats.

cancer biology↗

bioRxiv2021

Characterization and simulation of metagenomic nanopore sequencing data with Meta-NanoSim

Nanopore sequencing is crucial to metagenomic studies as its kilobase-long reads can contribute to resolving genomic structural differences among microbes. However, platform-specific challenges, including high base-call error rate, non-uniform read lengths, and the presence of chimeric artifacts, necessitate specifically designed analytical tools. Here, we present Meta-NanoSim, a fast and versatile utility that characterizes and simulates the unique properties of nanopore metagenomic reads. Further, Meta-NanoSim improves upon state-of-the-art methods on microbial abundance estimation through a base-level quantification algorithm. We demonstrate that Meta-NanoSim simulated data can facilitate the development of metagenomic algorithms and guide experimental design through a metagenomic assembly benchmarking task.

bioinformatics↗

bioRxiv2021

Characterizing stochastic cell cycle dynamics in exponential growth

Two powerful and complementary experimental approaches are commonly used to study the cell cycle and cell biology: One class of experiments characterizes the statistics (or demographics) of an unsynchronized exponentially-growing population, while the other captures cell cycle dynamics, either by time-lapse imaging of full cell cycles or in bulk experiments on synchronized populations. In this paper, we study the subtle relationship between observations in these two distinct experimental approaches. We begin with an existing model: a single-cell deterministic description of cell cycle dynamics where cell states (i.e. periods or phases) have precise lifetimes. We then generalize this description to a stochastic model in which the states have stochastic lifetimes, as described by arbitrary probability distribution functions. Our analyses of the demographics of an exponential culture reveal a simple and exact correspondence between the deterministic and stochastic models: The corresponding state lifetimes in the deterministic model are equal to the exponential mean of the lifetimes in the stochastic model. An important implication is therefore that the demographics of an exponential culture will be well-fit by a deterministic model even if the state timing is stochastic. Although we explore the implications of the models in the context of the Escherichia coli cell cycle, we expect both the models as well as the significance of the exponential-mean lifetimes to find many applications in the quantitative analysis of cell cycle dynamics in other biological systems.

biophysics↗

bioRxiv2021

LongStitch: High-quality genome assembly correction and scaffolding using long reads

BackgroundGenerating high-quality de novo genome assemblies is foundational to the genomics study of model and non-model organisms. In recent years, long-read sequencing has greatly benefited genome assembly and scaffolding, a process by which assembled sequences are ordered and oriented through the use of long-range information. Long reads are better able to span repetitive genomic regions compared to short reads, and thus have tremendous utility for resolving problematic regions and helping generate more complete draft assemblies. Here, we present LongStitch, a scalable pipeline that corrects and scaffolds draft genome assemblies exclusively using long reads. ResultsLongStitch incorporates multiple tools developed by our group and runs in up to three stages, which includes initial assembly correction (Tigmint-long), followed by two incremental scaffolding stages (ntLink and ARKS-long). Tigmint-long and ARKS-long are misassembly correction and scaffolding utilities, respectively, previously developed for linked reads, that we adapted for long reads. Here, we describe the LongStitch pipeline and introduce our new long-read scaffolder, ntLink, which utilizes lightweight minimizer mappings to join contigs. LongStitch was tested on short and long-read assemblies of three different human individuals using corresponding nanopore long-read data, and improves the contiguity of each assembly from 2.0-fold up to 304.6-fold (as measured by NGA50 length). Furthermore, LongStitch generates more contiguous and correct assemblies compared to state-of-the-art long-read scaffolder LRScaf in most tests, and consistently runs in under five hours using less than 23GB of RAM. ConclusionsDue to its effectiveness and efficiency in improving draft assemblies using long reads, we expect LongStitch to benefit a wide variety of de novo genome assembly projects. The LongStitch pipeline is freely available at https://github.com/bcgsc/longstitch.

bioinformatics↗

bioRxiv2021

Daily transient coating of the intestine leads to weight loss and improved glucose tolerance

The worsening obesity epidemic has driven a parallel increase in incidence of type-2 diabetes (T2D) found in 13% of the adult US population. Roux-en-Y gastric bypass surgery (RYGB) is the golden standard surgical treatment for obesity-related T2D. However, over 70% of T2D patient do not meet the NIH criteria for surgery, and many that do, are reluctant to consider such an invasive intervention. Mechanisms behind the antidiabetic effect of RYGB are not clearly understood, but isolation of proximal bowel from nutrient exposure plays a critical role. In this study, we tested the impact of daily administration of an oral gut coating agent, LuCI (Luminal Coating of the Intestine), in controlling weight and insulin resistance. LuCI is not systemically absorbed and provides a transient coating of the proximal intestines and excludes the coated bowel from nutrient contact, thus mimicking the effects of RYGB. We demonstrate that LuCI results in weight loss and improved insulin sensitivity in a rat DIO model. LuCI also appears to replicate hormonal changes seen after RYGB, by increasing post-prandial GLP-1 and GIP levels. LuCI has the potential to replicate the metabolic benefit of surgery and be a novel therapeutic strategy for obesity associated T2D.

bioengineering↗

bioRxiv2021

Noise Reconstruction & Removal Network: A New Architecture to Denoise FIB-SEM Images

Recent advances in Focused Ion Beam-Scanning Electron Microscopy (FIB-SEM) allows the imaging and analysis of cellular ultrastructure at nanoscale resolution, but the collection of labels and/or noise-free data sets has several challenges, often immutable. Reasons range from time consuming manual annotations, requiring highly trained specialists, to introducing imaging artifacts from the prolonged scanning during acquisition. We propose a fully unsupervised Noise Reconstruction and Removal Network for denoising scanning electron microscopy images. The architecture, inspired by gated recurrent units, reconstructs and removes the noise by synthesizing the sequential data. At the same time the fully unsupervised training guides the network in distinguishing true signal from noise and gives comparable results to supervised architectures. We demonstrate that this new network specialized on 3D electron microscopy data sets, achieves comparable and even better results than supervised networks.

bioengineering↗

bioRxiv2021

Restored TDCA and Valine Levels Imitate the Effects of Bariatric Surgery

Obesity is widespread and linked to various co-morbidities. Bariatric surgery has been identified as the only effective treatment, promoting sustained weight loss and the remission of co-morbidities. We performed sleeve-gastrectomies (SGx) in a pre-clinical mouse model of diet-induced obesity (DIO), delineating the effects on long-term remission from obesity. SGx resulted in sustained weight loss and improved glucose tolerance. Mass-spectrometric metabolomic profiling revealed significantly reduced systemic levels of taurodeoxycholic acid (TDCA) and L-valine in DIO mice. Notably, TDCA and L-Valine levels were restored after SGx in both human and mice to levels comparable with lean controls. Strikingly, combined systemic treatment with TDCA and valine induced a profound weight loss in DIO mice analogous to effects observed after SGx. Utilizing indirect calorimetry, we confirmed reduced food intake as causal for TDCA/valine-mediated weight loss via a central inhibition of the melanin-concentrating hormone. In summary, we identified restored TDCA/valine levels as an underlying mechanism of SGx-derived effects on weight loss. Of translational relevance, TDCA and L-valine are presented as novel agents promoting weight loss while reversing obesity-associated metabolic disorders.

cell biology↗

bioRxiv2018

Yeast Genomic Screens Identify Kinesins as Potential Targets of the Pseudomonas syringae Type III Effector, HopZ1a

Gram-negative bacterial pathogens inject type III secreted effectors (T3SEs) directly into host cells to promote pathogen fitness by manipulating host cellular processes. Despite their crucial role in promoting virulence, relatively few T3SEs have well-characterized enzymatic activities or host targets. This is in part due to functional redundancy within pathogen T3SE repertoires as well as promiscuous individual T3SEs that can have multiple host targets. To overcome these challenges, we conducted heterologous genetic screens in yeast, a non-host organism, to identify T3SEs that target conserved eukaryotic processes. We screened 75 T3SEs from the plant pathogen Pseudomonas syringae and identified 16 that inhibited yeast growth on rich media and eight that inhibited growth on stress-inducing media, including the acetyltransferase HopZ1a. We focused our further analysis on HopZ1a, which interacts with plant tubulin and alters microtubule networks. We first performed a Pathogenic Genetic Array (PGA) screen of HopZ1a against ~4400 yeast carrying non-essential mutations and found 95 and 10 deletion mutants which reduced or enhanced HopZ1a toxicity, respectively. To uncover putative HopZ1a host targets, we interrogated both the genetic- and physical-interaction profiles of HopZ1a by identifying yeast genes with PGA profiles most similar (i.e. congruent) to that of HopZ1a, performing a functional enrichment analysis of these HopZ1a-congruent genes, and by analyzing previously described HopZ physical interaction datasets. Finally, we demonstrated that HopZ1a can target kinesins by acetylating the plant kinesins HINKEL and MKRP1.\n\nARTICLE SUMMARYBacterial pathogens utilize secretion systems to directly deliver effector proteins into host cells, with the ultimate goal of promoting pathogen fitness. Despite the central role that effectors play in infection, the molecular function and host targets of most effectors remain uncharacterized. We used yeast genomics and protein interaction data to identify putative virulence targets of the effector HopZ1a from the plant pathogen Pseudomonas syringae. HopZ1a is an acetyltransferase that induces plant microtubule destruction. We showed that HopZ1a acetylated plant kinesin proteins known to regulate microtubule networks. Our study emphasizes the power of yeast functional genomic screens to characterize effector functions.

microbiology↗