Profiling SARS-CoV-2 HLA-I peptidome reveals T cell epitopes from out-of-frame ORFs.

T cell-mediated immunity plays an important role in controlling SARS-CoV-2 infection, but the repertoire of naturally processed and presented viral epitopes on class I human leukocyte antigen (HLA-I) remains uncharacterized. Here, we report the first HLA-I immunopeptidome of SARS-CoV-2 in two cell lines at different times post infection using mass spectrometry. We found HLA-I peptides derived not only from canonical open reading frames (ORFs) but also from internal out-of-frame ORFs in spike and nucleocapsid not captured by current vaccines. Some peptides from out-of-frame ORFs elicited T cell responses in a humanized mouse model and individuals with COVID-19 that exceeded responses to canonical peptides, including some of the strongest epitopes reported to date. Whole-proteome analysis of infected cells revealed that early expressed viral proteins contribute more to HLA-I presentation and immunogenicity. These biological insights, as well as the discovery of out-of-frame ORF epitopes, will facilitate selection of peptides for immune monitoring and vaccine development.

Genome annotation improvements from cross-phyla proteogenomics and time-of-day differences in malaria mosquito proteins using untargeted quantitative proteomics.

The malaria mosquito, Anopheles stephensi, and other mosquitoes modulate their biology to match the time-of-day. In the present work, we used a non-hypothesis driven approach (untargeted proteomics) to identify proteins in mosquito tissue, and then quantified the relative abundance of the identified proteins from An. stephensi bodies. Using these quantified protein levels, we then analyzed the data for proteins that were only detectable at certain times-of-the day, highlighting the need to consider time-of-day in experimental design. Further, we extended our time-of-day analysis to look for proteins which cycle in a rhythmic 24-hour ("circadian") manner, identifying 31 rhythmic proteins. Finally, to maximize the utility of our data, we performed a proteogenomic analysis to improve the genome annotation of An. stephensi. We compare peptides that were detected using mass spectrometry but are 'missing' from the An. stephensi predicted proteome, to reference proteomes from 38 other primarily human disease vector species. We found 239 such peptide matches and reveal that genome annotation can be improved using proteogenomic analysis from taxonomically diverse reference proteomes. Examination of 'missing' peptides revealed reading frame errors, errors in gene-calling, overlapping gene models, and suspected gaps in the genome assembly.

Mucosal Gene Expression in Pediatric and Adult Patients With Ulcerative Colitis Permits Modeling of Ideal Biopsy Collection Strategy for Transcriptomic Analysis.

Background: Transcriptional profiling has been performed on biopsies from ulcerative colitis patients. Limitations in prior studies include the variability introduced by inflammation, anatomic site of biopsy, extent of disease, and medications. We sought to more globally understand the variability of gene expression from patients with ulcerative colitis to advance our understanding of its pathogenesis and to guide clinical study design. Methods: We performed transcriptional profiling on 13 subjects, including pediatric and adult patients from 2 hospital sites. For each patient, we collected 6 biopsies from macroscopically inflamed tissue and 4 biopsies from macroscopically healthy-appearing tissue. Isolated RNA was used for microarray gene expression analysis utilizing Affymetrix Human Primeview microarrays. Ingenuity pathway analysis was used to assess over-representation of gene ontology and biological pathways. RNAseq was also performed, and differential analysis was assessed to compare affected vs unaffected samples. Finally, we modeled the minimum number of biopsies required to reliably detect gene expression across different subject numbers. Results: Transcriptional profiles co-clustered independently of the hospital collection site, patient age, sex, and colonic location, which parallels prior gene expression findings. A small set of genes not previously described was identified. Our modeling analysis reveals the number of biopsies and patients per cohort to yield reliable results in clinical studies. Conclusions: Key findings include concordance, including some expansion, of previously published gene expression studies and similarity among different age groups. We also established a reliable statistical model for biopsy collection for future clinical studies.

Uncovering Genomic Regions Associated with Trypanosoma Infections in Wild Populations of the Tsetse Fly Glossina fuscipes.

Vector-borne diseases are responsible for > 1 million deaths every year but genomic resources for most species responsible for their transmission are limited. This is true for neglected diseases such as sleeping sickness (Human African Trypanosomiasis), a disease caused by Trypanosoma parasites vectored by several species of tseste flies within the genus Glossina We describe an integrative approach that identifies statistical associations between trypanosome infection status of Glossina fuscipes fuscipes (Gff) flies from Uganda, for which functional studies are complicated because the species cannot be easily maintained in laboratory colonies, and ∼73,000 polymorphic sites distributed across the genome. Then, we identify candidate genes involved in Gff trypanosome susceptibility by taking advantage of genomic resources from a closely related species, G. morsitans morsitans (Gmm). We compiled a comprehensive transcript library from 72 published and unpublished RNAseq experiments of trypanosome-infected and uninfected Gmm flies, and improved the current Gmm transcriptome assembly. This new assembly was then used to enhance the functional annotations on the Gff genome. As a consequence, we identified 56 candidate genes in the vicinity of the 18 regions associated with Trypanosoma infection status in Gff Twenty-nine of these genes were differentially expressed (DE) among parasite-infected and uninfected Gmm, suggesting that their orthologs in Gff may correlate with disease transmission. These genes were involved in DNA regulation, neurophysiological functions, and immune responses. We highlight the power of integrating population and functional genomics from related species to enhance our understanding of the genetic basis of physiological traits, particularly in nonmodel organisms.

An algorithm for the classification of mRNA patterns in eosinophilic esophagitis: Integration of machine learning.

BACKGROUND: Diagnostic evaluation of eosinophilic esophagitis (EoE) remains difficult, particularly the assessment of the patient's allergic status. OBJECTIVE: This study sought to establish an automated medical algorithm to assist in the evaluation of EoE. METHODS: Machine learning techniques were used to establish a diagnostic probability score for EoE, p(EoE), based on esophageal mRNA transcript patterns from biopsies of patients with EoE, gastroesophageal reflux disease and controls. Dimensionality reduction in the training set established weighted factors, which were confirmed by immunohistochemistry. Following weighted factor analysis, p(EoE) was determined by random forest classification. Accuracy was tested in an external test set, and predictive power was assessed with equivocal patients. Esophageal IgE production was quantified with epsilon germ line (IGHE) transcripts and correlated with serum IgE and the Th2-type mRNA profile to establish an IGHE score for tissue allergy. RESULTS: In the primary analysis, a 3-class statistical model generated a p(EoE) score based on common characteristics of the inflammatory EoE profile. A p(EoE) ≥ 25 successfully identified EoE with high accuracy (sensitivity: 90.9%, specificity: 93.2%, area under the curve: 0.985) and improved diagnosis of equivocal cases by 84.6%. The p(EoE) changed in response to therapy. A secondary analysis loop in EoE patients defined an IGHE score of ≥37.5 for a patient subpopulation with increased esophageal allergic inflammation. CONCLUSIONS: The development of intelligent data analysis from a machine learning perspective provides exciting opportunities to improve diagnostic precision and improve patient care in EoE. The p(EoE) and the IGHE score are steps toward the development of decision trees to define EoE subpopulations and, consequently, will facilitate individualized therapy.

Patterns of Genome-Wide Variation in Glossina fuscipes fuscipes Tsetse Flies from Uganda.

The tsetse fly Glossina fuscipes fuscipes (Gff) is the insect vector of the two forms of Human African Trypanosomiasis (HAT) that exist in Uganda. Understanding Gff population dynamics, and the underlying genetics of epidemiologically relevant phenotypes is key to reducing disease transmission. Using ddRAD sequence technology, complemented with whole-genome sequencing, we developed a panel of ∼73,000 single-nucleotide polymorphisms (SNPs) distributed across the Gff genome that can be used for population genomics and to perform genome-wide-association studies. We used these markers to estimate genomic patterns of linkage disequilibrium (LD) in Gff, and used the information, in combination with outlier-locus detection tests, to identify candidate regions of the genome under selection. LD in individual populations decays to half of its maximum value (r(2) max/2) between 1359 and 2429 bp. The overall LD estimated for the species reaches r(2) max/2 at 708 bp, an order of magnitude slower than in Drosophila Using 53 infected (Trypanosoma spp.) and uninfected flies from four genetically distinct Ugandan populations adapted to different environmental conditions, we were able to identify SNPs associated with the infection status of the fly and local environmental adaptation. The extent of LD in Gff likely facilitated the detection of loci under selection, despite the small sample size. Furthermore, it is probable that LD in the regions identified is much higher than the average genomic LD due to strong selection. Our results show that even modest sample sizes can reveal significant genetic associations in this species, which has implications for future studies given the difficulties of collecting field specimens with contrasting phenotypes for association analysis.

Complex modulation of the Aedes aegypti transcriptome in response to dengue virus infection.

Dengue fever is the most important arboviral disease world-wide, with Aedes aegypti being the major vector. Interactions between the mosquito host and dengue viruses (DENV) are complex and vector competence varies among geographically-distinct Ae. aegypti populations. Additionally, dengue is caused by four antigenically-distinct viral serotypes (DENV1-4), each with multiple genotypes. Each virus genotype interacts differently with vertebrate and invertebrate hosts. Analyses of alterations in mosquito transcriptional profiles during DENV infection are expected to provide the basis for identifying networks of genes involved in responses to viruses and contribute to the molecular-genetic understanding of vector competence. In addition, this knowledge is anticipated to support the development of novel disease-control strategies. RNA-seq technology was used to assess genome-wide changes in transcript abundance at 1, 4 and 14 days following DENV2 infection in carcasses, midguts and salivary glands of the Ae. aegypti Chetumal strain. DENV2 affected the expression of 397 Ae. aegypti genes, most of which were down-regulated by viral infection. Differential accumulation of transcripts was mainly tissue- and time-specific. Comparisons of our data with other published reports reveal conservation of functional classes, but limited concordance of specific mosquito genes responsive to DENV2 infection. These results indicate the necessity of additional studies of mosquito-DENV interactions, specifically those focused on recently-derived mosquito strains with multiple dengue virus serotypes and genotypes.

Strain Variation in the Transcriptome of the Dengue Fever Vector, Aedes aegypti.

Studies of transcriptome dynamics provide a basis for understanding functional elements of the genome and the complexity of gene regulation. The dengue vector mosquito, Aedes aegypti, exhibits great adaptability to diverse ecological conditions, is phenotypically polymorphic, and shows variation in vectorial capacity to arboviruses. Previous genome sequencing showed richness in repetitive DNA and transposable elements that can contribute to genome plasticity. Population genetic studies revealed a varying degree of worldwide genetic polymorphism. However, the extent of functional genetic polymorphism across strains is unknown. The transcriptomes of three Ae. aegypti strains, Chetumal (CTM), Rexville D-Puerto Rico (Rex-D) and Liverpool (LVP), were compared. CTM is more susceptible than Rex- D to infection by dengue virus serotype 2. A total of 4188 transcripts exhibit either no or small variation (<2-fold) among sugar-fed samples of the three strains and between sugar- and blood-fed samples within each strain, corresponding most likely to genes encoding products necessary for vital functions. Transcripts enriched in blood-fed mosquitoes encode proteins associated with catalytic activities, molecular transport, metabolism of lipids, carbohydrates and amino acids, and functions related to blood digestion and the progression of the gonotropic cycle. Significant qualitative and quantitative differences were found in individual transcripts among strains including differential representation of paralogous gene products. The majority of immunity-associated transcripts decreased in accumulation after a bloodmeal and the results are discussed in relation to the different susceptibility of CTM and Rex-D mosquitoes to DENV2 infection.

RNA-seq analyses of blood-induced changes in gene expression in the mosquito vector species, Aedes aegypti.

BACKGROUND: Hematophagy is a common trait of insect vectors of disease. Extensive genome-wide transcriptional changes occur in mosquitoes after blood meals, and these are related to digestive and reproductive processes, among others. Studies of these changes are expected to reveal molecular targets for novel vector control and pathogen transmission-blocking strategies. The mosquito Aedes aegypti (Diptera, Culicidae), a vector of Dengue viruses, Yellow Fever Virus (YFV) and Chikungunya virus (CV), is the subject of this study to look at genome-wide changes in gene expression following a blood meal. RESULTS: Transcriptional changes that follow a blood meal in Ae. aegypti females were explored using RNA-seq technology. Over 30% of more than 18,000 investigated transcripts accumulate differentially in mosquitoes at five hours after a blood meal when compared to those fed only on sugar. Forty transcripts accumulate only in blood-fed mosquitoes. The list of regulated transcripts correlates with an enhancement of digestive activity and a suppression of environmental stimuli perception and innate immunity. The alignment of more than 65 million high-quality short reads to the Ae. aegypti reference genome permitted the refinement of the current annotation of transcript boundaries, as well as the discovery of novel transcripts, exons and splicing variants. Cis-regulatory elements (CRE) and cis-regulatory modules (CRM) enriched significantly at the 5'end flanking sequences of blood meal-regulated genes were identified. CONCLUSIONS: This study provides the first global view of the changes in transcript accumulation elicited by a blood meal in Ae. aegypti females. This information permitted the identification of classes of potentially co-regulated genes and a description of biochemical and physiological events that occur immediately after blood feeding. The data presented here serve as a basis for novel vector control and pathogen transmission-blocking strategies including those in which the vectors are modified genetically to express anti-pathogen effector molecules.

Comparative genomics allows the discovery of cis-regulatory elements in mosquitoes.

The discovery and mapping of cis-regulatory elements is important for understanding regulation of gene transcription in mosquito vectors of human diseases. Genome sequence data are available for 3 species, Aedes aegypti, Anopheles gambiae, and Culex quinquefasciatus (Diptera: Culicidae), representing 2 subfamilies (Culicinae and Anophelinae) that are estimated to have diverged 145 to 200 million years ago. Comparative genomics tools were used to screen genomic DNA fragments located in the 5'-end flanking regions of orthologous genes. These analyses resulted in the identification of 137 sequences, designated "mosquito motifs," 7 to 9 nucleotides in length, representing 18 families of putative cis-regulatory elements conserved significantly among the 3 species when compared to the fruit fly, Drosophila melanogaster. Forty-one of the motifs were implicated previously in experiments as sites for binding transcription factors or functioning in the regulation of mosquito gene expression. Further analyses revealed associations between specific motifs and expression profiles, particularly in those genes that show increased or decreased mRNA abundance in females following a blood meal, and those accumulating transcription products exclusively or preferentially in the midgut, fat bodies, or ovaries. These results validate the methodology and support a relationship between the discovered motifs and the conservation of hematophagy in mosquitoes.

Developmental expression patterns of cuticular protein genes with the R&R Consensus from Anopheles gambiae.

CPR proteins are the largest cuticular protein family in arthropods. The whole genome sequence of Anopheles gambiae revealed 156 genes that code for proteins with the R&R Consensus and named CPRs. This protein family can be divided into RR-1 and RR-2 subgroups, postulated to contribute to different regions of the cuticle. We determined the temporal expression patterns of these genes throughout post-embryonic development by means of real-time qRT-PCR. Based on expression profiles, these genes were grouped into 21 clusters. Most of the genes were expressed with sharp peaks at single or multiple periods associated with molting. Genes coding for RR-1 and RR-2 proteins were found together in several co-expression clusters. Twenty-five genes were expressed exclusively at one metamorphic stage. Five out of six X-linked genes showed equal expression in males and females, supporting the presence of a gene dosage compensation system in A. gambiae. Many RR-2 genes are organized into sequence clusters whose members are extremely similar to each other and generally closely associated on a chromosome. Most genes in each sequence cluster are expressed with the same temporal expression pattern and at the same level, suggesting a shared mechanism to regulate their expression.

Annotation and analysis of a large cuticular protein family with the R&R Consensus in Anopheles gambiae.

BACKGROUND: The most abundant family of insect cuticular proteins, the CPR family, is recognized by the R&R Consensus, a domain of about 64 amino acids that binds to chitin and is present throughout arthropods. Several species have now been shown to have more than 100 CPR genes, inviting speculation as to the functional importance of this large number and diversity. RESULTS: We have identified 156 genes in Anopheles gambiae that code for putative cuticular proteins in this CPR family, over 1% of the total number of predicted genes in this species. Annotation was verified using several criteria including identification of TATA boxes, INRs, and DPEs plus support from proteomic and gene expression analyses. Two previously recognized CPR classes, RR-1 and RR-2, form separate, well-supported clades with the exception of a small set of genes with long branches whose relationships are poorly resolved. Several of these outliers have clear orthologs in other species. Although both clades are under purifying selection, the RR-1 variant of the R&R Consensus is evolving at twice the rate of the RR-2 variant and is structurally more labile. In contrast, the regions flanking the R&R Consensus have diversified in amino-acid composition to a much greater extent in RR-2 genes compared with RR-1 genes. Many genes are found in compact tandem arrays that may include similar or dissimilar genes but always include just one of the two classes. Tandem arrays of RR-2 genes frequently contain subsets of genes coding for highly similar proteins (sequence clusters). Properties of the proteins indicated that each cluster may serve a distinct function in the cuticle. CONCLUSION: The complete annotation of this large gene family provides insight on the mechanisms of gene family evolution and clues about the need for so many CPR genes. These data also should assist annotation of other Anopheles genes.

Proteomic analysis of cast cuticles from Anopheles gambiae by tandem mass spectrometry.

Identification of authenticated cuticular proteins has been based on isolation and sequencing of individual proteins extracted from cleaned cuticles. These data facilitated classification of sequences from conceptual translation of cDNA or genomic sequences. The question arises whether such putative cuticular proteins actually are incorporated into the cuticle. This paper describes the profiling of cuticular proteins from Anopheles gambiae starting with cuticle cleaned by the insect itself in the course of molting. Proteins extracted from cast larval head capsules and cast pupal cuticles were fractionated by 1D SDS gel electrophoresis. Large gel slices were reduced, carbamidomethylated and digested with trypsin. The pellet remaining after SDS extraction was also treated with trypsin. The resulting peptides were separated on a C18 column and then analyzed by tandem mass spectrometry. Two-hundred-ninety-five peptides from putative cuticular proteins were identified; these corresponded to a minimum of 69 and a maximum of 119 different proteins. Each is reported as an authentic Anopheles cuticular protein for the first time. In addition to members of two known cuticular protein families, members of additional families likely to be structural components of the cuticle were identified. Furthermore, other peptides were identified that can be attributed to molting fluid, muscle and sclerotizing agents.