Biology subjects

Mann, M.

Publications and source records attributed to Mann, M..

At least 91 records · Page 5Linked to original sources

bioRxiv2022

Synchro-PASEF allows precursor-specific fragment ion extraction and interference removal in data-independent acquisition

Data-independent acquisition (DIA) methods have become increasingly popular in mass spectrometry (MS)-based proteomics because they enable continuous acquisition of fragment spectra for all precursors simultaneously. However, these advantages come with the challenge of correctly reconstructing the precursor-fragment relationships in these highly convoluted spectra for reliable identification and quantification. Here we introduce a scan mode for the combination of trapped ion mobility spectrometry (TIMS) with parallel accumulation - serial fragmentation (PASEF) that seamlessly and continuously follows the natural shape of the ion cloud in ion mobility and peptide precursor mass dimensions. Termed synchro-PASEF, it increases the detected fragment ion current several-fold at sub-second cycle times. Consecutive quadrupole selection windows move synchronously through the mass and ion mobility range, defining precursor-quadrupole relationships. In this process, the quadrupole slices through the peptide precursors, which separates fragment ion signals of each precursor into adjacent synchro-PASEF scans. This precisely defines precursor - fragment relationships in ion mobility and mass dimensions and effectively deconvolutes the DIA fragment space. Importantly, the partitioned parts of the fragment ion transitions provide a further dimension of specificity via a lock and key mechanism. This is also advantageous for quantification, where signals from interfering precursors in the DIA selection window do not affect all partitions of the fragment ion, allowing to retain only the specific parts for quantification. Overall, we establish the defining features of synchro-PASEF and explore its potential for proteomic analyses.

biochemistry↗

bioRxiv2022

McIdas localizes at centrioles and controls centriole numbers through PLK4-dependent phosphorylation

The centriole duplication cycle must be tightly controlled and coordinated with the chromosome cycle. Aberrations in centriole biogenesis can lead to cancer, developmental disorders and ciliopathies. Here, we show that McIdas -previously implicated in cell cycle control and centriole amplification in multiciliated cells-is critical to maintain centriole numbers. Using expansion microscopy, we demonstrate that McIdas is present at the middle part of centrioles, where it exhibits a differential localization during the cell cycle. McIdas loss perturbs daughter centriole biogenesis and centrosomal SAS6 recruitment, whereas its overexpression induces centriole overduplication. Consistently, McIdas depletion reduces PLK4-induced centriole amplification. McIdas interacts with and is phosphorylated by PLK4 in multiple sites identified by mass spectrometry. Mutational analysis shows that McIdas phosphorylation is important for centriole number control. Overall, our results identify a novel, direct role of McIdas on centriole duplication that can link its previously characterized roles in the chromosome cycle and multiciliogenesis.

molecular biology↗

bioRxiv2022

Proteogenomic analysis reveals RNA as an important source for tumor-agnostic neoantigen identification correlating with T-cell infiltration

Systemic pan-tumor analyses may reveal the significance of common features implicated in cancer immunogenicity and patient survival. Here, we provide a comprehensive multi-omics data set for 32 patients across 25 tumor types by combining proteogenomics with phenotypic and functional analyses. By using an optimized computational approach, we discovered a large number of novel tumor-specific and tumor-associated antigens including shared common target candidates. To create a pipeline for the identification of neoantigens in our cohort, we combined deep DNA and RNA sequencing with MS- based immunopeptidomics of tumor specimens, followed by the assessment of their immunogenicity. In fact, we could detect a broad variety of non-wild type HLA-binding peptides in the majority of patients and confirmed the immunogenicity of 24 neoantigens. Most interestingly, the majority of total and immunogenic neoantigens originated from variants identified in the RNA dataset, illustrating the importance of RNA as a still understudied source of cancer antigens. Moreover, the amount of these mainly RNA-based immunogenic neoantigens correlated positively with overall CD8+ tumor-infiltrating T cells. This study therefore underlines the importance of RNA-centered variant detection for the identification of shared biomarkers and potentially relevant neoantigen candidates. Statement of significanceThe significance of this study lies not only in the potential of our optimized proteogenomic workflow for the discovery of neoantigens (in particular RNA-derived neoantigens) for clinical application, but sheds light on the entity-agnostic prevalence of HLA class I peptide presentation of RNA processing events to be used for tumor targeting.

cancer biology↗

bioRxiv2022

Comprehensive chromatin proteomics resolves functional phases of pluripotency

The establishment of cellular identity is driven by transcriptional and epigenetic regulation exerted by the components of the chromatin proteome - the chromatome. However, chromatome composition and its dynamics in functional phases of pluripotency have not been comprehensively analyzed thus limiting our understanding of these processes. To address this problem, we developed an accurate mass spectrometry (MS)-based proteomic method called Chromatin Aggregation Capture (ChAC) followed by Data-Independent Acquisition (DIA) to analyze chromatome reorganizations during the transition from ground to formative and primed pluripotency states. This allowed us to generate a comprehensive atlas of proteomes, chromatomes, and chromatin affinities for the three pluripotency phases, revealing the specific binding and rearrangement of regulatory complexes. The technical advances, the comprehensive chromatome atlas, and the extensive analysis reported here provide a foundation for an in-depth understanding of mechanisms that govern the phased progression of pluripotency and changes of cellular identities in development and disease.

biochemistry↗

bioRxiv2022

AlphaPeptDeep: A modular deep learning framework to predict peptide properties for proteomics

Machine learning and in particular deep learning (DL) are increasingly important in mass spectrometry (MS)-based proteomics. Recent DL models can predict the retention time, ion mobility and fragment intensities of a peptide just from the amino acid sequence with good accuracy. However, DL is a very rapidly developing field with new neural network architectures frequently appearing, which are challenging to incorporate for proteomics researchers. Here we introduce AlphaPeptDeep, a modular Python framework built on the PyTorch DL library that learns and predicts the properties of peptides (https://github.com/MannLabs/alphapeptdeep). It features a model shop that enables non-specialists to create models in just a few lines of code. AlphaPeptDeep represents post-translational modifications in a generic manner, even if only the chemical composition is known. Extensive use of transfer learning obviates the need for large data sets to refine models for particular experimental conditions. The AlphaPeptDeep models for predicting retention time, collisional cross sections and fragment intensities are at least on par with existing tools. Additional sequence-based properties can also be predicted by AlphaPeptDeep, as demonstrated with a novel HLA peptide prediction model to improve HLA peptide identification for data-independent acquisition.

bioinformatics↗

bioRxiv2022

AlphaViz: Visualization and validation of critical proteomics data directly at the raw data level

Although current mass spectrometry (MS)-based proteomics identifies and quantifies thousands of proteins and (modified) peptides, only a minority of them are subjected to in-depth downstream analysis. With the advent of automated processing workflows, biologically or clinically important results within a study are rarely validated by visualization of the underlying raw information. Current tools are often not integrated into the overall analysis nor readily extendable with new approaches. To remedy this, we developed AlphaViz, an open-source Python package to superimpose output from common analysis workflows on the raw data for easy visualization and validation of protein and peptide identifications. AlphaViz takes advantage of recent breakthroughs in the deep learning-assisted prediction of experimental peptide properties to allow manual assessment of the expected versus measured peptide result. We focused on the visualization of the 4-dimensional data cuboid provided by Bruker TimsTOF instruments, where the ion mobility dimension, besides intensity and retention time, can be predicted and used for verification. We illustrate how AlphaViz can quickly validate or invalidate peptide identifications regardless of the score given to them by automated workflows. Furthermore, we provide a predict mode that can locate peptides present in the raw data but not reported by the search engine. This is illustrated the recovery of missing values from experimental replicates. Applied to phosphoproteomics, we show how key signaling nodes can be validated to enhance confidence for downstream interpretation or follow-up experiments. AlphaViz follows standards for open-source software development and features an easy-to-install graphical user interface for end-users and a modular Python package for bioinformaticians. Validation of critical proteomics results should now become a standard feature in MS-based proteomics.

bioinformatics↗

bioRxiv2022

Rapid and in-depth coverage of the (phospho-)proteome with deep libraries and optimal window design for dia-PASEF

Data-independent acquisition (DIA) methods have become increasingly attractive in mass spectrometry (MS)-based proteomics, because they enable high data completeness and a wide dynamic range. Recently, we combined DIA with parallel accumulation - serial fragmentation (dia-PASEF) on a Bruker trapped ion mobility separated (TIMS) quadrupole time-of-flight (TOF) mass spectrometer. This requires alignment of the ion mobility separation with the downstream mass selective quadrupole, leading to a more complex scheme for dia-PASEF window placement compared to DIA. To achieve high data completeness and deep proteome coverage, here we employ variable isolation windows that are placed optimally depending on precursor density in the m/z and ion mobility plane. This Automatic Isolation Design procedure is implemented in the freely available py_diAID package. In combination with in-depth project-specific proteomics libraries and the Evosep LC system, we reproducibly identified over 7,700 proteins in a human cancer cell line in 44 minutes with quadruplicate single-shot injections at high sensitivity. Even at a throughput of 100 samples per day (11 minutes LC gradients), we consistently quantified more than 6,000 proteins in mammalian cell lysates by injecting four replicates. We found that optimal dia-PASEF window placement facilitates in-depth phosphoproteomics with very high sensitivity, quantifying more than 35,000 phosphosites in a human cancer cell line stimulated with an epidermal growth factor (EGF) in triplicate 21 minutes runs. This covers a substantial part of the regulated phosphoproteome with high sensitivity, opening up for extensive systems-biological studies.

biochemistry↗

bioRxiv2022

The H2A.Z.1/PWWP2A/NuRD-associated protein HMG20A controls early head and heart developmental transcription programs

Abstract/SummarySpecialized chromatin-binding proteins are required for DNA-based processes during development. We recently established PWWP2A as direct histone variant H2A.Z interactor involved in mitosis and cranial-facial development. Here, we identify the H2A.Z/PWWP2A-associated protein HMG20A as part of several chromatin-modifying complexes including NuRD, and show that it localizes to genomic regulatory regions. Hmg20a depletion causes severe head and heart developmental defects in Xenopus laevis. Our data indicate that craniofacial malformations are caused by defects in neural crest cell (NCC) migration and cartilage formation. These developmental defects are pheno-copied in HMG20A-depleted mESCs, which show inefficient differentiation into NCCs and cardiomyocytes (CMs). Accordingly, loss of HMG20A caused striking deregulation of transcription programs involved in epithelial- mesenchymal transition (EMT) and cardiac differentiation, thereby providing insights into the regulatory circuits controlled by HMG20A. Collectively, our findings implicate HMG20A as part of the H2A.Z/PWWP2A/NuRD-axis and reveal it as a key modulator of the intricate developmental transcription programs that guide NCC and cardiomyocyte differentiation.

molecular biology↗

bioRxiv2022

Mitochondrial phosphoproteomes are functionally specialized across tissues

Mitochondria are essential organelles involved in critical biological processes such as energy metabolism and cell survival. Their dysfunction is linked to numerous human pathologies that often manifest in a tissue-specific manner. Accordingly, mitochondrial fitness depends on versatile proteomes specialized to meet diverse tissue-specific requirements. Furthermore, increasing evidence suggests that phosphorylation may also play an important role in regulating tissue-specific mitochondrial functions and pathophysiology. We hypothesized that recent advances in mass spectrometry (MS)-based proteomics would now enable in-depth measurement to quantitatively profile mitochondrial proteomes along with their matching phosphoproteomes across tissues. We isolated mitochondria from mouse heart, skeletal muscle, brown adipose tissue, kidney, liver, brain, and spleen by differential centrifugation followed by separation on Percoll gradients and high-resolution MS analysis of the proteomes and phosphoproteomes. This in-depth map substantially quantifies known and predicted mitochondrial proteins and provides a resource of core and tissue modulated mitochondrial proteins (mitophos.de). We also uncover tissue-specific repertoires of dozens of kinases and phosphatases. Predicting kinase substrate associations for different mitochondrial compartments indicates tissue-specific regulation at the phosphoproteome level. Illustrating the functional value of our resource, we reproduce mitochondrial phosphorylation events on DRP1 responsible for its mitochondrial recruitment and fission initiation and describe phosphorylation clusters on MIGA2 linked to mitochondrial fusion.

biochemistry↗

bioRxiv2022

The structural context of PTMs at a proteome wide scale

The recent revolution in computational protein structure prediction provides folding models for entire proteomes, which can now be integrated with large-scale experimental data. Mass spectrometry (MS)-based proteomics has identified and quantified tens of thousands of post-translational modifications (PTMs), most of them of uncertain functional relevance. In this study, we determine the structural context of these PTMs and investigate how this information can be leveraged to pinpoint potential regulatory sites. Our analysis uncovers global patterns of PTM occurrence across folded and intrinsically disordered regions. We found that this information can help to distinguish regulatory PTMs from those marking improperly folded proteins. Interestingly, the human proteome contains thousands of proteins that have large folded domains linked by short, unstructured regions that are strongly enriched in regulatory phosphosites. These include well-known kinase activation loops that induce protein conformational changes upon phosphorylation. This regulatory mechanism appears to be widespread in kinases but also occurs in other protein families such as solute carriers. It is not limited to phosphorylation but includes ubiquitination and acetylation sites as well. Furthermore, we performed three-dimensional proximity analysis which revealed examples of spatial co-regulation of different PTM types and potential PTM crosstalk. To enable the community to build upon these first analyses, we provide tools for 3D visualization of proteomics data and PTMs as well as python libraries for data accession and processing.

systems biology↗

bioRxiv2022

Distinct Core Glycan and O-Glycoform Utilization of SARS-CoV-2 Omicron Variant Spike Protein RBD Revealed by Top-Down Mass Spectrometry

The SARS-CoV-2 Omicron (B.1.1.529) variant possesses numerous spike (S) mutations particularly in the S receptor-binding domain (S-RBD) that significantly improve transmissibility and evasion of neutralizing antibodies. But exactly how the mutations in the Omicron variant enhance viral escape from immunological protection remains to be understood. The S-RBD remains the principal target for neutralizing antibodies and therapeutics, thus new structural insights into the Omicron S-RBD and characterization of the post-translational glycosylation changes can inform rational design of vaccines and therapeutics. Here we report the molecular variations and O-glycoform changes of the Omicron S-RBD variant as compared to wild-type (WA1/2020) and Delta (B.1.617.2) variants using high-resolution top-down mass spectrometry (MS). A novel O-glycosite (Thr376) unique to the Omicron variant is identified. Moreover, we have directly quantified the Core 1 and Core 2 O-glycan structures and characterized the O-glycoform structural heterogeneity of the three variants. Our findings reveal high resolution detail of Omicron O-glycoforms and their utilization to provide direct molecular evidence of proteoform alterations in the Omicron variant which could shed light on how this variant escapes immunological protection.

biochemistry↗

bioRxiv2022

Dynamic human liver proteome atlas reveals functional insights into disease pathways

Deeper understanding of liver pathophysiology would benefit from a comprehensive quantitative proteome resource at cell-type resolution to predict outcome and design therapy. Here, we quantify more than 150,000 sequence-unique peptides aggregated into 10,000 proteins across total liver, the major liver cell types, time-course of primary cell cultures and liver disease states. Bioinformatic analysis reveals that half of hepatocyte protein mass is comprised of enzymes and 23% of mitochondrial proteins, twice the proportion of other liver cell types. Using primary cell cultures, we capture dynamic proteome remodeling from tissue states to cell line states, providing useful information for biological or pharmaceutical research. Our extensive data serves as spectral library to characterize a human cohort of non-alcoholic steatohepatitis and cirrhosis. Dramatic proteome changes in liver tissue include signatures of stellate cell activation resembling liver cirrhosis and providing functional insights. We built a web-based dashboard application for the interactively exploration of our resource. HighlightsO_LICell-type resolved liver proteome with copy numbers for 10,500 proteins C_LIO_LITime-course of human liver primary cells uncovers functional proteome shifts C_LIO_LIA human cohort study reveals liver proteome changes in NASH and cirrhosis C_LIO_LIAn interactive web portal integrates the results for easy exploration C_LI

systems biology↗

bioRxiv2022

Direct DNA sequencing of "Candidatus Liberibacter asiaticus" from Diaphorina citri, the Asian citrus psyllid, and its implications for citrus greening disease management

The Asian citrus psyllid, Diaphorina citri is an invasive insect 1 and a vector of Candidatus Liberibacter asiaticus (CLas), a bacterium whose growth in Citrus species results in citrus greening disease 2,3. Methods to enrich and sequence CLas from D. citri often rely on biased genome amplification 4 and nevertheless contain significant quantities of host DNA 5,6. To overcome these hurdles, we developed a simple pre-treatment DNase and filtration (hereafter PDF) protocol to directly sequence CLas and the complete, primarily uncultivable, microbiome from D. citri adults. The PDF protocol yielded CLas abundances upwards of 60% and enabled detection of 156 genetic variants in these strains compared to progenitor strains in Florida, which included prophage encoding regions with key functions in CLas pathogenesis, putative antibiotic resistance loci, and a single secreted effector. These variants suggest laboratory propagation of CLas may result in different phenotypic trajectories among laboratories, and may confound CLas physiology or therapeutic design and evaluation if these differences remain undocumented. Finally, we obtained genetic signatures affiliated with Citrus nuclear and organellar genomes, entomopathogenic fungal mitochondria, and commensal bacteria from laboratory-reared and field-collected D. citri adults. Hence, the PDF protocol can inform agricultural management strategies related to pathogen evolution 7, insect microbiome surveillance 8, antibiotic resistance screening 9, and gut content analysis 10.

microbiology↗

bioRxiv2022

Profiling of the human intestinal microbiome and bile acids under physiologic conditions using an ingestible sampling device

The spatiotemporal structure of the human microbiome and metabolome reflects and determines regional intestinal physiology and may have implications for disease. Yet, we know little about the distribution of microbes and their products in the gut because of reliance on stool samples and limited access only to some regions of the gut using endoscopy in fasting or sedated individuals. To address these deficiencies, we developed and evaluated a safe, ingestible device that collects samples from multiple regions of the human intestinal tract during normal digestion. The collection of 240 intestinal samples from 15 healthy individuals using the device revealed significant differences between microbes and metabolites present in the intestines versus stool. Certain microbial taxa were differentially enriched, and bile acid profiles varied along the intestines and were highly distinct from those of stool. Correlations between gradients in bile acid concentrations and microbial abundance predicted species that altered the bile acid pool through deconjugation. Overall, we identified heterogeneous intestinal profiles of bacterial taxa and metabolites indicating that non-invasive multi-regional sampling of the intestinal tract under physiological conditions can help elucidate the roles of the gut microbiome and metabolome in human physiology and disease.

microbiology↗

bioRxiv2022

Differential UBE2H-CTLH E2-E3 ubiquitylation modules regulate erythroid maturation

The development of haematopoietic stem cells into mature erythrocytes - erythropoiesis - is a controlled process characterized by cellular reorganisation and drastic reshaping of the proteome landscape. Failure of ordered erythropoiesis is associated with anaemias and haematological malignancies. Although the ubiquitin (UB) system is a known crucial post-translational regulator in erythropoiesis, how the erythrocyte is reshaped by the UB system is poorly understood. By measuring the proteomic landscape of in vitro human erythropoiesis models, we found dynamic differential expression of subunits of the CTLH E3 ubiquitin ligase complex that formed distinct maturation stage-dependent assemblies of structurally homologous RANBP9-and RANBP10-CTLH complexes. Moreover, protein abundance of CTLHs cognate E2-conjugating enzyme UBE2H increased during terminal differentiation, which depended on catalytically active CTLH E3 complexes. CRISPR-Cas9 mediated inactivation of all CTLH E3 assemblies by targeting the catalytic subunit MAEA, or UBE2H, triggered spontaneous and accelerated maturation of erythroid progenitor cells including increased heme and haemoglobin synthesis. Thus, the orderly progression of human erythropoiesis is controlled by the assembly of distinct UBE2H-CTLH modules functioning at different developmental stages.

cell biology↗

bioRxiv2021

Proteomics of spatially identified tissues in whole organs

Spatial molecular profiling of complex tissues is essential to investigate cellular function in physiological and pathological states. However, methods for molecular analysis of biological specimens imaged in 3D as a whole are lacking. Here, we present DISCO-MS, a technology combining whole-organ imaging, deep learning-based image analysis, and ultra-high sensitivity mass spectrometry. DISCO-MS yielded qualitative and quantitative proteomics data indistinguishable from uncleared samples in both rodent and human tissues. Using DISCO-MS, we investigated microglia activation locally along axonal tracts after brain injury and revealed known and novel biomarkers. Furthermore, we identified initial individual amyloid-beta plaques in the brains of a young familial Alzheimers disease mouse model, characterized the core proteome of these aggregates, and highlighted their compositional heterogeneity. Thus, DISCO-MS enables quantitative, unbiased proteome analysis of target tissues following unbiased imaging of entire organs, providing new diagnostic and therapeutic opportunities for complex diseases, including neurodegeneration. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/466753v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@1e37035org.highwire.dtl.DTLVardef@dbaa98org.highwire.dtl.DTLVardef@19cece1org.highwire.dtl.DTLVardef@183c032_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIDISCO-MS combines tissue clearing, whole-organ imaging, deep learning-based image analysis, and ultra-high sensitivity mass spectrometry C_LIO_LIDISCO-MS yielded qualitative and quantitative proteomics data indistinguishable from fresh tissues C_LIO_LIDISCO-MS enables identification of rare pathological regions & their subsequent molecular analysis C_LIO_LIDISCO-MS revealed core proteome of plaques in 6 weeks old Alzheimer s disease mouse model Supplementary Video can be seen at: http://discotechnologies.org/DISCO-MS/ C_LI

bioengineering↗

bioRxiv2021

The social architecture of an in-depth cellular protein interactome

Nearly all cellular functions are mediated by protein-protein interactions and mapping the interactome provides fundamental insights into the regulation and structure of biological systems. In principle, affinity purification coupled to mass spectrometry (AP-MS) is an ideal and scalable tool, however, it has been difficult to identify low copy number complexes, membrane complexes and those disturbed by protein-tagging. As a result, our current knowledge of the interactome is far from complete, and assessing the reliability of reported interactions is challenging. Here we develop a sensitive, high-throughput, and highly reproducible AP-MS technology combined with a quantitative two-dimensional analysis strategy for comprehensive interactome mapping of Saccharomyces cerevisiae. We reduced required cell culture volumes thousand-fold and employed 96-well formats throughout, allowing replicate analysis of the endogenous green fluorescent protein (GFP) tagged library covering the entire expressed yeast proteome. The 4159 pull-downs generated a highly structured network of 3,909 proteins connected by 29,710 interactions. Compared to previous large-scale studies, we double the number of proteins (nodes in the network) and triple the number of reliable interactions (edges), including very low abundant epigenetic complexes, organellar membrane complexes and non-taggable complexes interfered by abundance correlation. This nearly saturated interactome reveals that the vast majority of yeast proteins are highly connected, with an average of 15 interactors, the majority of them unreported so far. Similar to social networks between humans, the average shortest distance is 4.2 interactions. A web portal (www.yeast-interactome.org) enables exploration of our dataset by the network and biological communities and variations of our AP-MS technology can be employed in any organism or dynamic conditions.

systems biology↗

bioRxiv2021

Quantification of new and archived Diaphorina citri transcriptome data using a chromosomal length D. citri genome assembly reveals the vector's tissue-specific transcriptional response to citrus greening disease

Background Huanglongbing (HLB) is the most serious disease of citrus. HLB is caused by the obligate, intracellular bacterium "Candidatus Liberibacter asiaticus" (CLas). CLas is transmitted by Diaphorina citri, the Asian citrus psyllid. Development of transmission blocking strategies to manage HLB relies on knowledge of CLas-D. citri interactions at the molecular level. Prior transcriptome analyses of CLas-infected and un-infected D. citri point to changes in psyllid biology due to CLas-infection. These studies relied on incomplete versions of the D. citri genome, lacked proper host plant controls, and/or were analyzed using different statistical approaches. Therefore, we used standardized experimental and computational approaches to identify differentially expressed genes in both CLas (+) and CLas (-) D. citri. The comparative analysis utilized the newest chromosomal length D. citri genome assembly Diaci_v3. In this work, we present a quantitative transcriptome analysis of excised heads, salivary glands, midguts and bacteriomes from CLas (+) and CLas (-) insects. Results Each organ had unique transcriptome profiles and responses to CLas infection. Though most psyllids were infected with CLas, CLas-derived transcripts were not detected in all organs. By analyzing the midgut dataset using both the Diaci_v1.1 and v3.0 D. citri genomes, we showed that improved genome assembly led to significant and quantifiable differences in RNAseq data interpretation. Conclusions Our results support the hypothesis that future transcriptome studies on circulative, vector-borne pathogens should be conducted at the tissue specific level using complete, chromosomal-length genome assemblies for the most accurate understanding of pathogen-induced changes in vector gene expression.

genomics↗