Perturbed liver gene zonation in a mouse model of non-alcoholic steatohepatitis.

Liver zonation characterizes the separation of metabolic pathways along the lobules and is required for optimal hepatic function. Wnt signaling is a master regulator of spatial liver zonation. A perivenous-periportal Wnt activity gradient orchestrates metabolic zonation by activating gene expression in perivenous hepatocytes, while suppressing gene expression in their periportal counterparts. However, the understanding as to the liver gene zonation and zonation regulators in diseases is limited. Non-alcoholic steatohepatitis (NASH) is a chronic liver disease characterized by fat accumulation, inflammation, and fibrosis. Here, we investigated the perturbation of liver gene zonation in a mouse NASH model by combining spatial transcriptomics, bulk RNAseq and in situ hybridization. Wnt-target genes represented a major subset of genes showing altered spatial expression in the NASH liver. The altered Wnt-target gene expression levels and zonation spatial patterns were in line with the up regulation of Wnt regulators and the augmentation of Wnt signaling. Particularly, we found that the Wnt activator Rspo3 expression was restricted to the perivenous zone in control liver but expanded to the periportal zone in NASH liver. AAV8-mediated RSPO3 overexpression in controls resulted in zonation changes, and further amplified the disturbed zonation of Wnt-target genes in NASH, similarly Rspo3 knockdown in Rspo3+/- mice resulted in zonation changes of Wnt-target genes in both chow and HFD mouse. Interestingly, there were no impacts on steatosis, inflammation, or fibrosis NASH pathology from RSPO3 overexpression nor Rspo3 knockdown. In summary, our study demonstrated the alteration of Wnt signaling in a mouse NASH model, leading to perturbed liver zonation.

Defining a Unique Gene Expression Profile in Mature and Developing Keloids.

Keloids are benign, fibroproliferative dermal tumors that typically form owing to abnormal wound healing. The current standard of care is generally ineffective and does not prevent recurrence. To characterize keloid scars and better understand the mechanism of their formation, we performed transcriptomic profiling of keloid biopsies from a total of 25 subjects of diverse racial and ethnic origins, 15 of whom provided a paired nonlesional sample, a longitudinal sample, or both. The transcriptomic signature of nonlesional skin biopsies from subjects with keloids resembled that of control skin at baseline but shifted to closely match that of keloid skin after dermal trauma. Peripheral keloid skin and rebiopsied surrounding normal skin both showed upregulation of epithelial-mesenchymal transition markers, extracellular matrix organization, and collagen genes. These keloid signatures strongly overlapped those from healthy wound healing studies, usually with greater perturbations, reinforcing our understanding of keloids as dysregulated and exuberant wound healing. In addition, 219 genes uniquely regulated in keloids but not in normal injured or uninjured skin were also identified. This study provides insights into mature and developing keloid signatures that can act as a basis for further validation and target identification in the search for transformative keloid treatments.

Spontaneous single-nucleotide substitutions and microsatellite mutations have distinct distributions of fitness effects: Distributions of fitness effects of spontaneous mutations.

The fitness effects of new mutations determine key properties of evolutionary processes. Beneficial mutations drive evolution, yet selection is also shaped by the frequency of small-effect deleterious mutations, whose combined effect can burden otherwise adaptive lineages and alter evolutionary trajectories and outcomes in clonally evolving organisms such as viruses, microbes, and tumors. The small effect sizes of these important mutations have made accurate measurements of their rates difficult. In microbes, assessing the effect of mutations on growth can be especially instructive, as this complex phenotype is closely linked to fitness in clonally evolving organisms. Here, we perform high-throughput time-lapse microscopy on cells from mutation-accumulation strains to precisely infer the distribution of mutational effects on growth rate in the budding yeast, Saccharomyces cerevisiae. We show that mutational effects on growth rate are overwhelmingly negative, highly skewed towards very small effect sizes, and frequent enough to suggest that deleterious hitchhikers may impose a significant burden on evolving lineages. By using lines that accumulated mutations in either wild-type or slippage repair-defective backgrounds, we further disentangle the effects of two common types of mutations, single-nucleotide substitutions and simple sequence repeat indels, and show that they have distinct effects on yeast growth rate. Although the average effect of a simple sequence repeat mutation is very small (~0.3%), many do alter growth rate, implying that this class of frequent mutations has an important evolutionary impact.

Urinary Single-Cell Profiling Captures the Cellular Diversity of the Kidney.

BACKGROUND: Microscopic analysis of urine sediment is probably the most commonly used diagnostic procedure in nephrology. The urinary cells, however, have not yet undergone careful unbiased characterization. METHODS: Single-cell transcriptomic analysis was performed on 17 urine samples obtained from five subjects at two different occasions, using both spot and 24-hour urine collection. A pooled urine sample from multiple healthy individuals served as a reference control. In total 23,082 cells were analyzed. Urinary cells were compared with human kidney and human bladder datasets to understand similarities and differences among the observed cell types. RESULTS: Almost all kidney cell types can be identified in urine, such as podocyte, proximal tubule, loop of Henle, and collecting duct, in addition to macrophages, lymphocytes, and bladder cells. The urinary cell-type composition was subject specific and reasonably stable using different collection methods and over time. Urinary cells clustered with kidney and bladder cells, such as urinary podocytes with kidney podocytes, and principal cells of the kidney and urine, indicating their similarities in gene expression. CONCLUSIONS: A reference dataset for cells in human urine was generated. Single-cell transcriptomics enables detection and quantification of almost all types of cells in the kidney and urinary tract.

Multifactorial heterogeneity of virus-specific T cells and association with the progression of human chronic hepatitis B infection.

Associations between chronic antigen stimulation, T cell dysfunction, and the expression of various inhibitory receptors are well characterized in several mouse and human systems. During chronic hepatitis B virus (HBV) infection (CHB), T cell responses are blunted with low frequencies of virus-specific T cells observed, making these parameters difficult to study. Here, using mass cytometry and a highly multiplexed combinatorial peptide-major histocompatibility complex (pMHC) tetramer strategy that allows for the detection of rare antigen-specific T cells, we simultaneously probed 484 unique HLA-A*1101-restricted epitopes spanning the entire HBV genome on T cells from patients at various stages of CHB. Numerous HBV-specific T cell populations were detected, validated, and profiled. T cells specific for two epitopes (HBVpol387 and HBVcore169) displayed differing and complex heterogeneities that were associated with the disease progression, and the expression of inhibitory receptors on these cells was not linearly related with their extent of T cell dysfunction. For HBVcore169-specific CD8+ T cells, we found cellular markers associated with long-term memory, polyfunctionality, and the presence of several previously unidentified public TCR clones that correlated with viral control. Using high-dimensional trajectory analysis of these cellular phenotypes, a pseudo-time metric was constructed that fit with the status of viral infection in corresponding patients. This was validated in a longitudinal cohort of patients undergoing antiviral therapy. Our study uncovers complex relationships of inhibitory receptors between the profiles of antigen-specific T cells and the status of CHB with implications for new strategies of therapeutic intervention.

Patterns of mutation within an emerging endemic lineage of HEV-3a.

The hepatitis E virus can cause chronic infections in immuno-suppressed patients, and cases have been on the rise globally. Viral mutations during such infections are difficult to characterize. We deep-sequenced viral populations from 15 immunocompromised patients with chronic HEV to identify the viral lineage and describe viral mutational hotspots within and across patients. A total of 21 viral RNA samples were collected between 2012 and 2017 from a single hospital in Singapore. Sequences covering a total of 3894 bp of the HEV genome were obtained. Phylogenetic analyses identified all sequences as belonging to the HEV-3a sub-clade and clearly indicate a unique local lineage. Deep sequencing reveals variable viral population complexity during infections. Comparisons of viral samples from the same patients spaced 2-19 months apart revealed rapid nucleotide replacements in the dominant viral sequence in both ribavirin treated and treatment-naive patients. Mutational hotspots were identified within ORF3 and the PCP/HVR domain of ORF1.

Induction of Human T-cell and Cytokine Responses Following Vaccination with a Novel Influenza Vaccine.

Cell mediated immunity plays a vital role in defense against influenza infection in humans. Less is known about the role of vaccine-induced cell mediated immunity and the cytokine responses elicited. We measured CD4+ and CD8+ T-cell reactivity in human subjects following vaccination with licensed trivalent influenza vaccine and a novel virus-like particle based vaccine. We detected influenza-specific CD4+ T-cell responses following vaccination with the licensed trivalent influenza vaccine and found that these correlated with antibody measurements. Administration of the novel virus-like particle based vaccine elicited influenza-specific CD4+ and CD8+ T-cell responses and the induction of the cytokines IFN-γ, IL-17A, IL17F, IL-5, IL-13, IL-9, IL-10 and IL-21. Pre-existing cytokine responses influenced the profile of the cytokine response elicited by vaccination. In a subset of individuals the VLP vaccine changed pre-vaccination production of type 2 cytokines such as IL-5 and IL-13 to a post-vaccination type 1 cytokine signature characterized by IFN-γ. A transcriptional signature to vaccination was found to correlate with antibody titer, IFN-γ production by T-cells and expression of a putative RNA helicase, DDX17, on the surface of immune cells.

Single-virion sequencing of lamivudine-treated HBV populations reveal population evolution dynamics and demographic history.

BACKGROUND: Viral populations are complex, dynamic, and fast evolving. The evolution of groups of closely related viruses in a competitive environment is termed quasispecies. To fully understand the role that quasispecies play in viral evolution, characterizing the trajectories of viral genotypes in an evolving population is the key. In particular, long-range haplotype information for thousands of individual viruses is critical; yet generating this information is non-trivial. Popular deep sequencing methods generate relatively short reads that do not preserve linkage information, while third generation sequencing methods have higher error rates that make detection of low frequency mutations a bioinformatics challenge. Here we applied BAsE-Seq, an Illumina-based single-virion sequencing technology, to eight samples from four chronic hepatitis B (CHB) patients - once before antiviral treatment and once after viral rebound due to resistance. RESULTS: With single-virion sequencing, we obtained 248-8796 single-virion sequences per sample, which allowed us to find evidence for both hard and soft selective sweeps. We were able to reconstruct population demographic history that was independently verified by clinically collected data. We further verified four of the samples independently through PacBio SMRT and Illumina Pooled deep sequencing. CONCLUSIONS: Overall, we showed that single-virion sequencing yields insight into viral evolution and population dynamics in an efficient and high throughput manner. We believe that single-virion sequencing is widely applicable to the study of viral evolution in the context of drug resistance and host adaptation, allows differentiation between soft or hard selective sweeps, and may be useful in the reconstruction of intra-host viral population demographic history.

Extremely Rare Polymorphisms in Saccharomyces cerevisiae Allow Inference of the Mutational Spectrum.

The characterization of mutational spectra is usually carried out in one of three ways-by direct observation through mutation accumulation (MA) experiments, through parent-offspring sequencing, or by indirect inference from sequence data. Direct observations of spontaneous mutations with MA experiments are limited, given (i) the rarity of spontaneous mutations, (ii) applicability only to laboratory model species with short generation times, and (iii) the possibility that mutational spectra under lab conditions might be different from those observed in nature. Trio sequencing is an elegant solution, but it is not applicable in all organisms. Indirect inference, usually from divergence data, faces no such technical limitations, but rely upon critical assumptions regarding the strength of natural selection that are likely to be violated. Ideally, new mutational events would be directly observed before the biased filter of selection, and without the technical limitations common to lab experiments. One approach is to identify very young mutations from population sequencing data. Here we do so by leveraging two characteristics common to all new mutations-new mutations are necessarily rare in the population, and absent in the genomes of immediate relatives. From 132 clinical yeast strains, we were able to identify 1,425 putatively new mutations and show that they exhibit extremely low signatures of selection, as well as display a mutational spectrum that is similar to that identified by a large scale MA experiment. We verify that population sequencing data are a potential wealth of information for inferring mutational spectra, and should be considered for analysis where MA experiments are infeasible or especially tedious.

Selection Transforms the Landscape of Genetic Variation Interacting with Hsp90.

The protein-folding chaperone Hsp90 has been proposed to buffer the phenotypic effects of mutations. The potential for Hsp90 and other putative buffers to increase robustness to mutation has had major impact on disease models, quantitative genetics, and evolutionary theory. But Hsp90 sometimes contradicts expectations for a buffer by potentiating rapid phenotypic changes that would otherwise not occur. Here, we quantify Hsp90's ability to buffer or potentiate (i.e., diminish or enhance) the effects of genetic variation on single-cell morphological features in budding yeast. We corroborate reports that Hsp90 tends to buffer the effects of standing genetic variation in natural populations. However, we demonstrate that Hsp90 tends to have the opposite effect on genetic variation that has experienced reduced selection pressure. Specifically, Hsp90 tends to enhance, rather than diminish, the effects of spontaneous mutations and recombinations. This result implies that Hsp90 does not make phenotypes more robust to the effects of genetic perturbation. Instead, natural selection preferentially allows buffered alleles to persist and thereby creates the false impression that Hsp90 confers greater robustness.

Transcriptional Profiling of Mycobacterium tuberculosis Exposed to In Vitro Lysosomal Stress.

Increasing experimental evidence supports the idea that Mycobacterium tuberculosis has evolved strategies to survive within lysosomes of activated macrophages. To further our knowledge of M. tuberculosis response to the hostile lysosomal environment, we profiled the global transcriptional activity of M. tuberculosis when exposed to the lysosomal soluble fraction (SF) prepared from activated macrophages. Transcriptome sequencing (RNA-seq) analysis was performed using various incubation conditions, ranging from noninhibitory to cidal based on the mycobacterial replication or killing profile. Under inhibitory conditions that led to the absence of apparent mycobacterial replication, M. tuberculosis expressed a unique transcriptome with modulation of genes involved in general stress response, metabolic reprogramming, respiration, oxidative stress, dormancy response, and virulence. The transcription pattern also indicates characteristic cell wall remodeling with the possible outcomes of increased infectivity, intrinsic resistance to antibiotics, and subversion of the host immune system. Among the lysosome-specific responses, we identified the glgE-mediated 1,4 α-glucan synthesis pathway and a defined group of VapBC toxin/anti-toxin systems, both of which represent toxicity mechanisms that potentially can be exploited for killing intracellular mycobacteria. A meta-analysis including previously reported transcriptomic studies in macrophage infection and in vitro stress models was conducted to identify overlapping and nonoverlapping pathways. Finally, the Tap efflux pump-encoding gene Rv1258c was selected for validation. An M. tuberculosis ΔRv1258c mutant was constructed and displayed increased susceptibility to killing by lysosomal SF and the antimicrobial peptide LL-37, as well as attenuated survival in primary murine macrophages and human macrophage cell line THP-1.

Whole Genome Analysis of 132 Clinical Saccharomyces cerevisiae Strains Reveals Extensive Ploidy Variation.

Budding yeast has undergone several independent transitions from commercial to clinical lifestyles. The frequency of such transitions suggests that clinical yeast strains are derived from environmentally available yeast populations, including commercial sources. However, despite their important role in adaptive evolution, the prevalence of polyploidy and aneuploidy has not been extensively analyzed in clinical strains. In this study, we have looked for patterns governing the transition to clinical invasion in the largest screen of clinical yeast isolates to date. In particular, we have focused on the hypothesis that ploidy changes have influenced adaptive processes. We sequenced 144 yeast strains, 132 of which are clinical isolates. We found pervasive large-scale genomic variation in both overall ploidy (34% of strains identified as 3n/4n) and individual chromosomal copy numbers (36% of strains identified as aneuploid). We also found evidence for the highly dynamic nature of yeast genomes, with 35 strains showing partial chromosomal copy number changes and eight strains showing multiple independent chromosomal events. Intriguingly, a lineage identified to be baker's/commercial derived with a unique damaging mutation in NDC80 was particularly prone to polyploidy, with 83% of its members being triploid or tetraploid. Polyploidy was in turn associated with a >2× increase in aneuploidy rates as compared to other lineages. This dataset provides a rich source of information on the genomics of clinical yeast strains and highlights the potential importance of large-scale genomic copy variation in yeast adaptation.

Precise estimates of mutation rate and spectrum in yeast.

Mutation is the ultimate source of genetic variation. The most direct and unbiased method of studying spontaneous mutations is via mutation accumulation (MA) lines. Until recently, MA experiments were limited by the cost of sequencing and thus provided us with small numbers of mutational events and therefore imprecise estimates of rates and patterns of mutation. We used whole-genome sequencing to identify nearly 1,000 spontaneous mutation events accumulated over ∼311,000 generations in 145 diploid MA lines of the budding yeast Saccharomyces cerevisiae. MA experiments are usually assumed to have negligible levels of selection, but even mild selection will remove strongly deleterious events. We take advantage of such patterns of selection and show that mutation classes such as indels and aneuploidies (especially monosomies) are proportionately much more likely to contribute mutations of large effect. We also provide conservative estimates of indel, aneuploidy, environment-dependent dominant lethal, and recessive lethal mutation rates. To our knowledge, for the first time in yeast MA data, we identified a sufficiently large number of single-nucleotide mutations to measure context-dependent mutation rates and were able to (i) confirm strong AT bias of mutation in yeast driven by high rate of mutations from C/G to T/A and (ii) detect a higher rate of mutation at C/G nucleotides in two specific contexts consistent with cytosine methylation in S. cerevisiae.