Characterization of a new SARS-CoV-2 variant that emerged in Brazil.

The spike (S) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) plays a key role in viral infectivity. It is also the major antigen stimulating the host's protective immune response, specifically, the production of neutralizing antibodies. Recently, a new variant of SARS-CoV-2 possessing multiple mutations in the S protein, designated P.1, emerged in Brazil. Here, we characterized a P.1 variant isolated in Japan by using Syrian hamsters, a well-established small animal model for the study of SARS-CoV-2 disease (COVID-19). In hamsters, the variant showed replicative abilities and pathogenicity similar to those of early and contemporary strains (i.e., SARS-CoV-2 bearing aspartic acid [D] or glycine [G] at position 614 of the S protein). Sera and/or plasma from convalescent patients and BNT162b2 messenger RNA vaccinees showed comparable neutralization titers across the P.1 variant, S-614D, and S-614G strains. In contrast, the S-614D and S-614G strains were less well recognized than the P.1 variant by serum from a P.1-infected patient. Prior infection with S-614D or S-614G strains efficiently prevented the replication of the P.1 variant in the lower respiratory tract of hamsters upon reinfection. In addition, passive transfer of neutralizing antibodies to hamsters infected with the P.1 variant or the S-614G strain led to reduced virus replication in the lower respiratory tract. However, the effect was less pronounced against the P.1 variant than the S-614G strain. These findings suggest that the P.1 variant may be somewhat antigenically different from the early and contemporary strains of SARS-CoV-2.

Syrian hamsters as a small animal model for SARS-CoV-2 infection and countermeasure development.

At the end of 2019, a novel coronavirus (severe acute respiratory syndrome coronavirus 2; SARS-CoV-2) was detected in Wuhan, China, that spread rapidly around the world, with severe consequences for human health and the global economy. Here, we assessed the replicative ability and pathogenesis of SARS-CoV-2 isolates in Syrian hamsters. SARS-CoV-2 isolates replicated efficiently in the lungs of hamsters, causing severe pathological lung lesions following intranasal infection. In addition, microcomputed tomographic imaging revealed severe lung injury that shared characteristics with SARS-CoV-2-infected human lung, including severe, bilateral, peripherally distributed, multilobular ground glass opacity, and regions of lung consolidation. SARS-CoV-2-infected hamsters mounted neutralizing antibody responses and were protected against subsequent rechallenge with SARS-CoV-2. Moreover, passive transfer of convalescent serum to naïve hamsters efficiently suppressed the replication of the virus in the lungs even when the serum was administrated 2 d postinfection of the serum-treated hamsters. Collectively, these findings demonstrate that this Syrian hamster model will be useful for understanding SARS-CoV-2 pathogenesis and testing vaccines and antiviral drugs.

Mutations in the Neuraminidase-Like Protein of Bat Influenza H18N11 Virus Enhance Virus Replication in Mammalian Cells, Mice, and Ferrets.

To characterize bat influenza H18N11 virus, we propagated a reverse genetics-generated H18N11 virus in Madin-Darby canine kidney subclone II cells and detected two mammal-adapting mutations in the neuraminidase (NA)-like protein (NA-F144C and NA-T342A, N2 numbering) that increased the virus titers in three mammalian cell lines (i.e., Madin-Darby canine kidney, Madin-Darby canine kidney subclone II, and human lung adenocarcinoma [Calu-3] cells). In mice, wild-type H18N11 virus replicated only in the lungs of the infected animals, whereas the NA-T342A and NA-F144C/T342A mutant viruses were detected in the nasal turbinates, in addition to the lungs. Bat influenza viruses have not been tested for their virulence or organ tropism in ferrets. We detected wild-type and single mutant viruses each possessing NA-F144C or NA-T342A in the nasal turbinates of one or several infected ferrets, respectively. A mutant virus possessing both the NA-F144C and NA-T342A mutations was isolated from both the lung and the trachea, suggesting that it has a broader organ tropism than the wild-type virus. However, none of the H18N11 viruses caused symptoms in mice or ferrets. The NA-F144C/T342A double mutation did not substantially affect virion morphology or the release of virions from cells. Collectively, our data demonstrate that the propagation of bat influenza H18N11 virus in mammalian cells can result in mammal-adapting mutations that may increase the replicative ability and/or organ tropism of the virus; overall, however, these viruses did not replicate to high titers throughout the respiratory tract of mice and ferrets.IMPORTANCE Bats are reservoirs for several severe zoonotic pathogens. The genomes of influenza A viruses of the H17N10 and H18N11 subtypes have been identified in bats, but no live virus has been isolated. The characterization of artificially generated bat influenza H18N11 virus in mammalian cell lines and animal models revealed that this virus can acquire mammal-adapting mutations that may increase its zoonotic potential; however, the wild-type and mutant viruses did not replicate to high titers in all infected animals.

Mutations in the PA Protein of Avian H5N1 Influenza Viruses Affect Polymerase Activity and Mouse Virulence.

To study the influenza virus determinants of pathogenicity, we characterized two highly pathogenic avian H5N1 influenza viruses isolated in Vietnam in 2012 (A/duck/Vietnam/QT1480/2012 [QT1480]) and 2013 (A/duck/Vietnam/QT1728/2013 [QT1728]) and found that the activity of their polymerase complexes differed significantly, even though both viruses were highly pathogenic in mice. Further studies revealed that the PA-S343A/E347D (PA with the S-to-A change at position 343 and the E-to-D change at position 347) mutations reduced viral polymerase activity and mouse virulence when tested in the genetic background of QT1728 virus. In contrast, the PA-343S/347E mutations increased the polymerase activity of QT1480 and the virulence of a low-pathogenic H5N1 influenza virus. The PA-343S residue (which alone increased viral polymerase activity and mouse virulence significantly relative to viral replication complexes encoding PA-343A) is frequently found in H5N1 influenza viruses of several subclades; infection with a virus possessing this amino acid may pose an increased risk to humans.IMPORTANCE H5N1 influenza viruses cause severe infections in humans with a case fatality rate that exceeds 50%. The factors that determine the high virulence of these viruses in humans are not fully understood. Here, we identified two amino acid changes in the viral polymerase PA protein that affect the activity of the viral polymerase complex and virulence in mice. Infection with viruses possessing these amino acid changes may pose an increased risk to humans.

Development of high-yield influenza B virus vaccine viruses.

The burden of human infections with influenza A and B viruses is substantial, and the impact of influenza B virus infections can exceed that of influenza A virus infections in some seasons. Over the past few decades, viruses of two influenza B virus lineages (Victoria and Yamagata) have circulated in humans, and both lineages are now represented in influenza vaccines, as recommended by the World Health Organization. Influenza B virus vaccines for humans have been available for more than half a century, yet no systematic efforts have been undertaken to develop high-yield candidates. Therefore, we screened virus libraries possessing random mutations in the six "internal" influenza B viral RNA segments [i.e., those not encoding the major viral antigens, hemagglutinin (HA) and neuraminidase NA)] for mutants that confer efficient replication. Candidate viruses that supported high yield in cell culture were tested with the HA and NA genes of eight different viruses of the Victoria and Yamagata lineages. We identified combinations of mutations that increased the titers of candidate vaccine viruses in mammalian cells used for human influenza vaccine virus propagation and in embryonated chicken eggs, the most common propagation system for influenza viruses. These influenza B virus vaccine backbones can be used for improved vaccine virus production.

Lung-Derived Exosomal miR-483-3p Regulates the Innate Immune Response to Influenza Virus Infection.

Exosomes regulate cell-cell communication by transferring functional proteins and RNAs between cells. Here, to clarify the function of exosomes during influenza virus infection, we characterized lung-derived exosomal microRNAs (miRNAs). Among the detected miRNAs, miR-483-3p was present at high levels in bronchoalveolar lavage fluid (BALF) exosomes during infection of mice with various strains of influenza virus, and miR-483-3p transfection potentiated gene expression of type I interferon and proinflammatory cytokine upon viral infection of MLE-12 cells. RNF5, a regulator of the RIG-I signaling pathway, was identified as a target gene of miR-483-3p. Moreover, we found that CD81, another miR-483-3p target, functions as a negative regulator of RIG-I signaling in MLE-12 cells. Taken together, this study indicates that BALF exosomal miRNAs may mediate the antiviral and inflammatory response to influenza virus infection.

Combination Therapy With Neuraminidase and Polymerase Inhibitors in Nude Mice Infected With Influenza Virus.

Background: Treatment of immunocompromised, influenza virus-infected patients with the viral neuraminidase inhibitor oseltamivir often leads to the emergence of drug-resistant variants. Combination therapy with compounds that target different steps in the viral life cycle may improve treatment outcomes and reduce the emergence of drug-resistant variants. Methods: Here, we infected immunocompromised nude mice with an influenza A virus and treated them with neuraminidase (oseltamivir, laninamivir) or viral polymerase (favipiravir) inhibitors, or combinations thereof. Results: Combination therapy for 28 days increased survival times compared with monotherapy, but the animals died after treatment was terminated. Mono- and combination therapies did not consistently reduce lung virus titers. Prolonged viral replication led to the emergence of neuraminidase inhibitor-resistant variants, although viruses remained sensitive to favipiravir. Overall, favipiravir provided greater benefit than neuraminidase inhibitors. Conclusions: Collectively, our data demonstrate that combination therapy in immunocompromised hosts increases survival times, but does not suppress the emergence of neuraminidase inhibitor-resistant variants.

Effectiveness of Whole, Inactivated, Low Pathogenicity Influenza A(H7N9) Vaccine against Antigenically Distinct, Highly Pathogenic H7N9 Virus.

The recent emergence of highly pathogenic influenza A(H7N9) variants poses a great risk to humans. We show that ferrets vaccinated with low pathogenicity H7N9 virus vaccine do not develop severe symptoms after infection with an antigenically distinct, highly pathogenic H7N9 virus. These results demonstrate the protective benefits of this H7N9 vaccine.

Diversity of Influenza A(H5N1) Viruses in Infected Humans, Northern Vietnam, 2004-2010.

Influenza viruses exist in each host as a collection of genetically diverse variants, which might enhance their adaptive potential. To assess the genetic and functional diversity of highly pathogenic avian influenza A(H5N1) viruses within infected humans, we used deep-sequencing methods to characterize samples obtained from infected patients in northern Vietnam during 2004-2010 on different days after infection, from different anatomic sites, or both. We detected changes in virus genes that affected receptor binding, polymerase activity, or interferon antagonism, suggesting that these factors could play roles in influenza virus adaptation to humans. However, the frequency of most of these mutations remained low in the samples tested, implying that they were not efficiently selected within these hosts. Our data suggest that adaptation of influenza A(H5N1) viruses is probably stepwise and depends on accumulating combinations of mutations that alter function while maintaining fitness.

Emergence of Oseltamivir-Resistant H7N9 Influenza Viruses in Immunosuppressed Cynomolgus Macaques.

Antiviral compounds (eg, the neuraminidase inhibitor oseltamivir) are invaluable for the treatment of individuals infected with influenza A viruses of the H7N9 subtype (A[H7N9]), which have infected and killed hundreds of persons. However, oseltamivir treatment often leads to the emergence of resistant viruses in immunocompromised individuals. To better understand the emergence and properties of oseltamivir-resistant A(H7N9) viruses in immunosuppressed individuals, we infected immunosuppressed cynomolgus macaques with an A(H7N9) virus and treated them with oseltamivir. Disease severity and mortality were higher in immunosuppressed than in immunocompetent animals. Oseltamivir treatment at 2 different doses reduced A(H7N9) viral titers in infected animals, but even high-dose oseltamivir did not block viral replication sufficiently to suppress the emergence of resistant variants. Some resistant variants were not appreciably attenuated in cultured cells, but an oseltamivir-resistant A(H7N9) virus did not transmit among ferrets. These findings are useful for the control of A(H7N9) virus infections in clinical settings.

Integrating Transcriptomic and Proteomic Data Using Predictive Regulatory Network Models of Host Response to Pathogens.

Mammalian host response to pathogenic infections is controlled by a complex regulatory network connecting regulatory proteins such as transcription factors and signaling proteins to target genes. An important challenge in infectious disease research is to understand molecular similarities and differences in mammalian host response to diverse sets of pathogens. Recently, systems biology studies have produced rich collections of omic profiles measuring host response to infectious agents such as influenza viruses at multiple levels. To gain a comprehensive understanding of the regulatory network driving host response to multiple infectious agents, we integrated host transcriptomes and proteomes using a network-based approach. Our approach combines expression-based regulatory network inference, structured-sparsity based regression, and network information flow to infer putative physical regulatory programs for expression modules. We applied our approach to identify regulatory networks, modules and subnetworks that drive host response to multiple influenza infections. The inferred regulatory network and modules are significantly enriched for known pathways of immune response and implicate apoptosis, splicing, and interferon signaling processes in the differential response of viral infections of different pathogenicities. We used the learned network to prioritize regulators and study virus and time-point specific networks. RNAi-based knockdown of predicted regulators had significant impact on viral replication and include several previously unknown regulators. Taken together, our integrated analysis identified novel module level patterns that capture strain and pathogenicity-specific patterns of expression and helped identify important regulators of host response to influenza infection.

Molecular Determinants of Virulence and Stability of a Reporter-Expressing H5N1 Influenza A Virus.

UNLABELLED: We previously reported that an H5N1 virus carrying the Venus reporter gene, which was inserted into the NS gene segment from the A/Puerto Rico/8/1934(H1N1) virus (Venus-H5N1 virus), became more lethal to mice, and the reporter gene was stably maintained after mouse adaptation compared with the wild-type Venus-H5N1 (WT-Venus-H5N1) virus. However, the basis for this difference in virulence and Venus stability was unclear. Here, we investigated the molecular determinants behind this virulence and reporter stability by comparing WT-Venus-H5N1 virus with a mouse-adapted Venus-H5N1 (MA-Venus-H5N1) virus. To determine the genetic basis for these differences, we used reverse genetics to generate a series of reassortants of these two viruses. We found that reassortants with PB2 from MA-Venus-H5N1 (MA-PB2), MA-PA, or MA-NS expressed Venus more stably than did WT-Venus-H5N1 virus. We also found that a single mutation in PB2 (V25A) or in PA (R443K) increased the virulence of the WT-Venus-H5N1 virus in mice and that the presence of both of these mutations substantially enhanced the pathogenicity of the virus. Our results suggest roles for PB2 and PA in the stable maintenance of a foreign protein as an NS1 fusion protein in influenza A virus. IMPORTANCE: The ability to visualize influenza viruses has far-reaching benefits in influenza virus research. Previously, we reported that an H5N1 virus bearing the Venus reporter gene became more pathogenic to mice and that its reporter gene was more highly expressed and more stably maintained after mouse adaptation. Here, we investigated the molecular determinants behind this enhanced virulence and reporter stability. We found that mutations in PB2 (V25A) and PA (R443K) play crucial roles in the stable maintenance of a foreign protein as an NS1 fusion protein in influenza A virus and in the virulence of influenza virus in mice. Our findings further our knowledge of the pathogenicity of influenza virus in mammals and will help advance influenza virus-related live-imaging studies in vitro and in vivo.

Loss of Interleukin 1 Receptor Antagonist Enhances Susceptibility to Ebola Virus Infection.

The current outbreak of Ebola virus (EBOV) infection in West Africa is unprecedented, with nearly 26 000 confirmed cases and >10 000 deaths. Comprehensive data on the pathogenesis of EBOV infection are lacking; however, recent studies suggested that fatal EBOV infections are characterized by dysregulation of the innate immune response and a subsequent cytokine storm. Specifically, several studies suggested that hypersecretion of interleukin 1 receptor antagonist (IL-1Ra) correlates with lethal EBOV infections. To examine the significance of IL-1Ra in EBOV infections, we infected mice that lack the gene encoding IL-1Ra, Il1rn (IL-1RN-KO), and mice with wild-type Il1rn (IL-1RN-WT) with a mouse-adapted EBOV (MA-EBOV). Infected IL-1RN-KO mice lost more weight and had a lower survival rate than IL-1RN-WT mice infected with MA-EBOV. In addition, IL-1RN-KO mice infected with wild-type EBOV, which does not cause lethal infection in adult immunocompetent mice, such as C57BL/6 mice, experienced greater weight loss than IL-1RN-WT mice infected with wild-type EBOV. Further studies revealed that the levels of 6 cytokines in spleens-IL-1α, IL-1ß, interleukin 12p40, interleukin 17, granulocyte colony-stimulating factor, and regulated on activation, normal T-cell expressed and secreted-were significantly different between IL-1RN-KO mice and IL-1RN-WT mice infected with MA-EBOV. Collectively, our data suggest that IL-1Ra may have a protective effect upon EBOV infection, likely by damping an overactive proinflammatory immune response.

Adding protein context to the human protein-protein interaction network to reveal meaningful interactions.

Interactions of proteins regulate signaling, catalysis, gene expression and many other cellular functions. Therefore, characterizing the entire human interactome is a key effort in current proteomics research. This challenge is complicated by the dynamic nature of protein-protein interactions (PPIs), which are conditional on the cellular context: both interacting proteins must be expressed in the same cell and localized in the same organelle to meet. Additionally, interactions underlie a delicate control of signaling pathways, e.g. by post-translational modifications of the protein partners - hence, many diseases are caused by the perturbation of these mechanisms. Despite the high degree of cell-state specificity of PPIs, many interactions are measured under artificial conditions (e.g. yeast cells are transfected with human genes in yeast two-hybrid assays) or even if detected in a physiological context, this information is missing from the common PPI databases. To overcome these problems, we developed a method that assigns context information to PPIs inferred from various attributes of the interacting proteins: gene expression, functional and disease annotations, and inferred pathways. We demonstrate that context consistency correlates with the experimental reliability of PPIs, which allows us to generate high-confidence tissue- and function-specific subnetworks. We illustrate how these context-filtered networks are enriched in bona fide pathways and disease proteins to prove the ability of context-filters to highlight meaningful interactions with respect to various biological questions. We use this approach to study the lung-specific pathways used by the influenza virus, pointing to IRAK1, BHLHE40 and TOLLIP as potential regulators of influenza virus pathogenicity, and to study the signalling pathways that play a role in Alzheimer's disease, identifying a pathway involving the altered phosphorylation of the Tau protein. Finally, we provide the annotated human PPI network via a web frontend that allows the construction of context-specific networks in several ways.

Enhancing diagnostic accuracy of multiple myeloma through ML-driven analysis of hematological slides: new dataset and identification model to support hematologists.

Multiple Myeloma (MM) is a hematological malignancy characterized by the clonal proliferation of plasma cells within the bone marrow. Diagnosing MM presents considerable challenges, involving the identification of plasma cells in cytology examinations on hematological slides. At present, this is still a time-consuming manual task and has high labor costs. These challenges have adverse implications, which rely heavily on medical professionals' expertise and experience. To tackle these challenges, we present an investigation using Artificial Intelligence, specifically a Machine Learning analysis of hematological slides with a Deep Neural Network (DNN), to support specialists during the process of diagnosing MM. In this sense, the contribution of this study is twofold: in addition to the trained model to diagnose MM, we also make available to the community a fully-curated hematological slide dataset with thousands of images of plasma cells. Taken together, the setup we established here is a framework that researchers and hospitals with limited resources can promptly use. Our contributions provide practical results that have been directly applied in the public health system in Brazil. Given the open-source nature of the project, we anticipate it will be used and extended to diagnose other malignancies.

A graph-based machine learning framework identifies critical properties of FVIII that lead to hemophilia A.

Introduction: Blood coagulation is an essential process to cease bleeding in humans and other species. This mechanism is characterized by a molecular cascade of more than a dozen components activated after an injury to a blood vessel. In this process, the coagulation factor VIII (FVIII) is a master regulator, enhancing the activity of other components by thousands of times. In this sense, it is unsurprising that even single amino acid substitutions result in hemophilia A (HA)-a disease marked by uncontrolled bleeding and that leaves patients at permanent risk of hemorrhagic complications. Methods: Despite recent advances in the diagnosis and treatment of HA, the precise role of each residue of the FVIII protein remains unclear. In this study, we developed a graph-based machine learning framework that explores in detail the network formed by the residues of the FVIII protein, where each residue is a node, and two nodes are connected if they are in close proximity on the FVIII 3D structure. Results: Using this system, we identified the properties that lead to severe and mild forms of the disease. Finally, in an effort to advance the development of novel recombinant therapeutic FVIII proteins, we adapted our framework to predict the activity and expression of more than 300 in vitro alanine mutations, once more observing a close agreement between the in silico and the in vitro results. Discussion: Together, the results derived from this study demonstrate how graph-based classifiers can leverage the diagnostic and treatment of a rare disease.

Development of an Enhanced High-Yield Influenza Vaccine Backbone in Embryonated Chicken Eggs.

Vaccination is an efficient approach to preventing influenza virus infections. Recently, we developed influenza A and B virus vaccine backbones that increased the yield of several vaccine viruses in Madin-Darby canine kidney (MDCK) and African green monkey kidney (Vero) cells. These vaccine backbones also increased viral replication in embryonated chicken eggs, which are the most frequently used platform for influenza vaccine manufacturing. In this study, to further increase the viral titers in embryonated chicken eggs, we introduced random mutations into the 'internal genes' (i.e., all influenza viral genes except those encoding the hemagglutinin and neuraminidase proteins) of the influenza A virus high-yield virus backbone we developed previously. The randomly mutated viruses were sequentially passaged in embryonated chicken eggs to select variants with increased replicative ability. We identified a candidate that conferred higher influenza virus growth than the high-yield parental virus backbone. Although the observed increases in virus growth may be considered small, they are highly relevant for vaccine manufacturers.

Full-scale network analysis reveals properties of the FV protein structure organization.

Blood coagulation is a vital process for humans and other species. Following an injury to a blood vessel, a cascade of molecular signals is transmitted, inhibiting and activating more than a dozen coagulation factors and resulting in the formation of a fibrin clot that ceases the bleeding. In this process, the Coagulation factor V (FV) is a master regulator, coordinating critical steps of this process. Mutations to this factor result in spontaneous bleeding episodes and prolonged hemorrhage after trauma or surgery. Although the role of FV is well characterized, it is unclear how single-point mutations affect its structure. In this study, to understand the effect of mutations, we created a detailed network map of this protein, where each node is a residue, and two residues are connected if they are in close proximity in the three-dimensional structure. Overall, we analyzed 63 point-mutations from patients and identified common patterns underlying FV deficient phenotypes. We used structural and evolutionary patterns as input to machine learning algorithms to anticipate the effects of mutations and anticipated FV-deficiency with fair accuracy. Together, our results demonstrate how clinical features, genetic data and in silico analysis are converging to enhance treatment and diagnosis of coagulation disorders.

Computational analyses reveal fundamental properties of the AT structure related to thrombosis.

Summary: Blood coagulation is a vital process for humans and other species. Following an injury to a blood vessel, a cascade of molecular signals is transmitted, inhibiting and activating more than a dozen coagulation factors and resulting in the formation of a fibrin clot that ceases the bleeding. In this process, antithrombin (AT), encoded by the SERPINC1 gene is a key player regulating the clotting activity and ensuring that it stops at the right time. In this sense, mutations to this factor often result in thrombosis-the excessive coagulation that leads to the potentially fatal formation of blood clots that obstruct veins. Although this process is well known, it is still unclear why even single residue substitutions to AT lead to drastically different phenotypes. In this study, to understand the effect of mutations throughout the AT structure, we created a detailed network map of this protein, where each node is an amino acid, and two amino acids are connected if they are in close proximity in the three-dimensional structure. With this simple and intuitive representation and a machine-learning framework trained using genetic information from more than 130 patients, we found that different types of thrombosis have emerging patterns that are readily identifiable. Together, these results demonstrate how clinical features, genetic data and in silico analysis are converging to enhance the diagnosis and treatment of coagulation disorders. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

CTen: a web-based platform for identifying enriched cell types from heterogeneous microarray data.

BACKGROUND: Interpreting in vivo sampled microarray data is often complicated by changes in the cell population demographics. To put gene expression into its proper biological context, it is necessary to distinguish differential gene transcription from artificial gene expression induced by changes in the cellular demographics. RESULTS: CTen (cell type enrichment) is a web-based analytical tool which uses our highly expressed, cell specific (HECS) gene database to identify enriched cell types in heterogeneous microarray data. The web interface is designed for differential expression and gene clustering studies, and the enrichment results are presented as heatmaps or downloadable text files. CONCLUSIONS: In this work, we use an independent, cell-specific gene expression data set to assess CTen's performance in accurately identifying the appropriate cell type and provide insight into the suggested level of enrichment to optimally minimize the number of false discoveries. We show that CTen, when applied to microarray data developed from infected lung tissue, can correctly identify the cell signatures of key lymphocytes in a highly heterogeneous environment and compare its performance to another popular bioinformatics tool. Furthermore, we discuss the strong implications cell type enrichment has in the design of effective microarray workflow strategies and show that, by combining CTen with gene expression clustering, we may be able to determine the relative changes in the number of key cell types.CTen is available at http://www.influenza-x.org/~jshoemaker/cten/