Effect of human H3N2 influenza virus reassortment on influenza incidence and severity during the 2017-18 influenza season in the USA: a retrospective observational genomic analysis.

BACKGROUND: During the 2017-18 influenza season in the USA, there was a high incidence of influenza illness and mortality. However, no apparent antigenic change was identified in the dominant H3N2 viruses, and the severity of the season could not be solely attributed to a vaccine mismatch. We aimed to investigate whether the altered virus properties resulting from gene reassortment were underlying causes of the increased case number and disease severity associated with the 2017-18 influenza season. METHODS: Samples included were collected from patients with influenza who were prospectively recruited during the 2016-17 and 2017-18 influenza seasons at the Johns Hopkins Hospital Emergency Departments in Baltimore, MD, USA, as well as from archived samples from Johns Hopkins Health System sites. Among 647 recruited patients with influenza A virus infection, 411 patients with whole-genome sequences were available in the Johns Hopkins Center of Excellence for Influenza Research and Surveillance network during the 2016-17 and 2017-18 seasons. Phylogenetic trees were constructed based on viral whole-genome sequences. Representative viral isolates of the two seasons were characterised in immortalised cell lines and human nasal epithelial cell cultures, and patients' demographic data and clinical outcomes were analysed. FINDINGS: Unique H3N2 reassortment events were observed, resulting in two predominant strains in the 2017-18 season: HA clade 3C.2a2 and clade 3C.3a, which had novel gene segment constellations containing gene segments from HA clade 3C.2a1 viruses. The reassortant re3C.2a2 viruses replicated with faster kinetics and to a higher peak titre compared with the parental 3C.2a2 and 3C.2a1 viruses (48 h vs 72 h). Furthermore, patients infected with reassortant 3C.2a2 viruses had higher Influenza Severity Scores than patients infected with the parental 3C.2a2 viruses (median 3·00 [IQR 1·00-4·00] vs 1·50 [1·00-2·00]; p=0·018). INTERPRETATION: Our findings suggest that the increased severity of the 2017-18 influenza season was due in part to two intrasubtypes, cocirculating H3N2 reassortant viruses with fitness advantages over the parental viruses. This information could help inform future vaccine development and public health policies. FUNDING: The Center of Excellence for Influenza Research and Response in the US, National Science and Technology Council, and Chang Gung Memorial Hospital in Taiwan.

Dynamics of the Oral Microbiome During Initial Military Training at Fort Benning, Georgia.

INTRODUCTION: Military trainees are at increased risk for infectious disease outbreaks because of the unique circumstances of the training environment (e.g., close proximity areas and physiologic/psychologic stress). Standard medical countermeasures in military training settings include routine immunization (e.g., influenza and adenovirus) as well as chemoprophylaxis [e.g., benzathine penicillin G (Bicillin) for the prevention of group A streptococcal disease] for pathogens associated with outbreaks in these settings. In a population of U.S. Army Infantry trainees, we evaluated changes in the oral microbiome during a 14-week military training cycle. MATERIALS AND METHODS: Trainees were enrolled in an observational cohort study in 2015-2016. In 2015, Bicillin was administered to trainees to ameliorate the risk of group A Streptococcus outbreaks, whereas in 2016, trainees did not receive a Bicillin inoculation. Oropharyngeal swabs were collected from participants at days 0, 7, 14, 28, 56, and 90 of training. Swabs were collected, flash frozen, and stored. DNA was extracted from swabs, and amplicon sequencing of the 16s rRNA gene was performed. Microbiome dynamics were evaluated using the QIIME 2 workflow along with DADA2, SINA with SILVA, and an additional processing in R. RESULTS: We observed that microbiome samples from the baseline (day 0) visit were distinct from one another, whereas samples collected on day 14 exhibited significant microbiome convergence. Day 14 convergence was coincident with an increase in DNA sequences associated with Streptococcus, though there was not a significant difference between Streptococcus abundance over time between 2015 and 2016 (P = .07), suggesting that Bicillin prophylaxis did not significantly impact overall Streptococcus abundance. CONCLUSIONS: The temporary convergence of microbiomes is coincident with a rise in communicable infections in this population. The dynamic response of microbiomes during initial military training supports similar observations in the literature of transient convergence of the human microbiome under cohabitation in the time frame including in this experiment. This population and the associated longitudinal studies allow for controlled studies of human microbiome under diverse conditions.

Breast cancer cell mesenchymal transition and metastasis directed by DAP5/eIF3d-mediated selective mRNA translation.

Cancer cell plasticity enables cell survival in harsh physiological environments and fate transitions such as the epithelial-to-mesenchymal transition (EMT) that underlies invasion and metastasis. Using genome-wide transcriptomic and translatomic studies, an alternate mechanism of cap-dependent mRNA translation by the DAP5/eIF3d complex is shown to be essential for metastasis, EMT, and tumor directed angiogenesis. DAP5/eIF3d carries out selective translation of mRNAs encoding EMT transcription factors and regulators, cell migration integrins, metalloproteinases, and cell survival and angiogenesis factors. DAP5 is overexpressed in metastatic human breast cancers associated with poor metastasis-free survival. In human and murine breast cancer animal models, DAP5 is not required for primary tumor growth but is essential for EMT, cell migration, invasion, metastasis, angiogenesis, and resistance to anoikis. Thus, cancer cell mRNA translation involves two cap-dependent mRNA translation mechanisms, eIF4E/mTORC1 and DAP5/eIF3d. These findings highlight a surprising level of plasticity in mRNA translation during cancer progression and metastasis.

MutaGAN: A sequence-to-sequence GAN framework to predict mutations of evolving protein populations.

The ability to predict the evolution of a pathogen would significantly improve the ability to control, prevent, and treat disease. Machine learning, however, is yet to be used to predict the evolutionary progeny of a virus. To address this gap, we developed a novel machine learning framework, named MutaGAN, using generative adversarial networks with sequence-to-sequence, recurrent neural networks generator to accurately predict genetic mutations and evolution of future biological populations. MutaGAN was trained using a generalized time-reversible phylogenetic model of protein evolution with maximum likelihood tree estimation. MutaGAN was applied to influenza virus sequences because influenza evolves quickly and there is a large amount of publicly available data from the National Center for Biotechnology Information's Influenza Virus Resource. MutaGAN generated 'child' sequences from a given 'parent' protein sequence with a median Levenshtein distance of 4.00 amino acids. Additionally, the generator was able to generate sequences that contained at least one known mutation identified within the global influenza virus population for 72.8 per cent of parent sequences. These results demonstrate the power of the MutaGAN framework to aid in pathogen forecasting with implications for broad utility in evolutionary prediction for any protein population.

Optimization of Oxford Nanopore Technology Sequencing Workflow for Detection of Amplicons in Real Time Using ONT-DART Tool.

An optimized, well-tested and validated targeted genomic sequencing-based high-throughput assay is currently not available ready for routine biodefense and biosurveillance applications. Earlier, we addressed this gap by developing and establishing baseline comparisons of a multiplex end-point Polymerase Chain Reaction (PCR) assay followed by Oxford Nanopore Technology (ONT) based amplicon sequencing to real time PCR and customized data processing. Here, we expand upon this effort by identifying the optimal ONT library preparation method for integration into a novel software platform ONT-DART (ONT-Detection of Amplicons in Real-Time). ONT-DART is a dockerized, real-time, amplicon-sequence analysis workflow that is used to reproducibly process and filter read data to support actionable amplicon detection calls based on alignment metrics, within sample statistics, and no-template control data. This analysis pipeline was used to compare four ONT library preparation protocols using R9 and Flongle (FL) flow cells. The two 4-Primer methods tested required the shortest preparation times (5.5 and 6.5 h) for 48 libraries but provided lower fidelity data. The Native Barcoding and Ligation methods required longer preparation times of 8 and 12 h, respectively, and resulted in higher overall data quality. On average, data derived from R9 flow cells produced true positive calls for target organisms more than twice as fast as the lower throughput FL flow cells. These results suggest that utilizing the R9 flowcell with an ONT Native Barcoding amplicon library method in combination with ONT-DART platform analytics provides the best sequencing-based alternative to current PCR-based biodetection methods.

A DAP5/eIF3d alternate mRNA translation mechanism promotes differentiation and immune suppression by human regulatory T cells.

Regulatory T cells (Treg cells) inhibit effector T cells and maintain immune system homeostasis. Treg cell maturation in peripheral sites requires inhibition of protein kinase mTORC1 and TGF-beta-1 (TGF-beta). While Treg cell maturation requires protein synthesis, mTORC1 inhibition downregulates it, leaving unanswered how Treg cells achieve essential mRNA translation for development and immune suppression activity. Using human CD4+ T cells differentiated in culture and genome-wide transcription and translation profiling, here we report that TGF-beta transcriptionally reprograms naive T cells to express Treg cell differentiation and immune suppression mRNAs, while mTORC1 inhibition impairs translation of T cell mRNAs but not those induced by TGF-beta. Rather than canonical mTORC1/eIF4E/eIF4G translation, Treg cell mRNAs utilize the eIF4G homolog DAP5 and initiation factor eIF3d in a non-canonical translation mechanism that requires cap-dependent binding by eIF3d directed by Treg cell mRNA 5' noncoding regions. Silencing DAP5 in isolated human naive CD4+ T cells impairs their differentiation into Treg cells. Treg cell differentiation is mediated by mTORC1 downregulation and TGF-beta transcriptional reprogramming that establishes a DAP5/eIF3d-selective mechanism of mRNA translation.

Examining the effect of wound cleansing on the microbiome of venous stasis ulcers.

Common treatment for venous leg wounds includes topical wound dressings with compression. At each dressing change, wounds are debrided and washed; however, the effect of the washing procedure on the wound microbiome has not been studied. We hypothesized that wound washing may alter the wound microbiome. To characterize microbiome changes with respect to wound washing, swabs from 11 patients with chronic wounds were sampled before and after washing, and patient microbiomes were characterized using 16S rRNA sequencing and culturing. Microbiomes across patient samples prior to washing were typically polymicrobial but varied in the number and type of bacterial genera present. Proteus and Pseudomonas were the dominant genera in the study. We found that washing does not consistently change microbiome diversity but does cause consistent changes in microbiome composition. Specifically, washing caused a decrease in the relative abundance of the most highly represented genera in each patient cluster. The finding that venous leg ulcer wound washing, a standard of care therapy, can induce changes in the wound microbiome is novel and could be potentially informative for future guided therapy strategies.

Genomic diversity of SARS-CoV-2 during early introduction into the Baltimore-Washington metropolitan area.

The early COVID-19 pandemic was characterized by rapid global spread. In Maryland and Washington, DC, United States, more than 2500 cases were reported within 3 weeks of the first COVID-19 detection in March 2020. We aimed to use genomic sequencing to understand the initial spread of SARS-CoV-2 - the virus that causes COVID-19 - in the region. We analyzed 620 samples collected from the Johns Hopkins Health System during March 11-31, 2020, comprising 28.6% of the total cases in Maryland and Washington, DC. From these samples, we generated 114 complete viral genomes. Analysis of these genomes alongside a subsampling of over 1000 previously published sequences showed that the diversity in this region rivaled global SARS-CoV-2 genetic diversity at that time and that the sequences belong to all of the major globally circulating lineages, suggesting multiple introductions into the region. We also analyzed these regional SARS-CoV-2 genomes alongside detailed clinical metadata and found that clinically severe cases had viral genomes belonging to all major viral lineages. We conclude that efforts to control local spread of the virus were likely confounded by the number of introductions into the region early in the epidemic and the interconnectedness of the region as a whole.

A mixed community of skin microbiome representatives influences cutaneous processes more than individual members.

BACKGROUND: Skin, the largest organ of the human body by weight, hosts a diversity of microorganisms that can influence health. The microbial residents of the skin are now appreciated for their roles in host immune interactions, wound healing, colonization resistance, and various skin disorders. Still, much remains to be discovered in terms of the host pathways influenced by skin microorganisms, as well as the higher-level skin properties impacted through these microbe-host interactions. Towards this direction, recent efforts using mouse models point to pronounced changes in the transcriptional profiles of the skin in response to the presence of a microbial community. However, there is a need to quantify the roles of microorganisms at both the individual and community-level in healthy human skin. In this study, we utilize human skin equivalents to study the effects of individual taxa and a microbial community in a precisely controlled context. Through transcriptomics analysis, we identify key genes and pathways influenced by skin microbes, and we also characterize higher-level impacts on skin processes and properties through histological analyses. RESULTS: The presence of a microbiome on a 3D skin tissue model led to significantly altered patterns of gene expression, influencing genes involved in the regulation of apoptosis, proliferation, and the extracellular matrix (among others). Moreover, microbiome treatment influenced the thickness of the epidermal layer, reduced the number of actively proliferating cells, and increased filaggrin expression. Many of these findings were evident upon treatment with the mixed community, but either not detected or less pronounced in treatments by single microorganisms, underscoring the impact that a diverse skin microbiome has on the host. CONCLUSIONS: This work contributes to the understanding of how microbiome constituents individually and collectively influence human skin processes and properties. The results show that, while it is important to understand the effect of individual microbes on the host, a full community of microbes has unique and pronounced effects on the skin. Thus, in its impacts on the host, the skin microbiome is more than the sum of its parts. Video abstract.

Genomic Diversity of SARS-CoV-2 During Early Introduction into the United States National Capital Region.

BACKGROUND: The early COVID-19 pandemic has been characterized by rapid global spread. In the United States National Capital Region, over 2,000 cases were reported within three weeks of its first detection in March 2020. We aimed to use genomic sequencing to understand the initial spread of SARS-CoV-2, the virus that causes COVID-19, in the region. By correlating genetic information to disease phenotype, we also aimed to gain insight into any correlation between viral genotype and case severity or transmissibility. METHODS: We performed whole genome sequencing of clinical SARS-CoV-2 samples collected in March 2020 by the Johns Hopkins Health System. We analyzed these regional SARS-CoV-2 genomes alongside detailed clinical metadata and the global phylogeny to understand early establishment of the virus within the region. RESULTS: We analyzed 620 samples from the Johns Hopkins Health System collected between March 11-31, 2020, comprising 37.3% of the total cases in Maryland during this period. We selected 143 of these samples for sequencing, generating 114 complete viral genomes. These genomes belong to all five major Nextstrain-defined clades, suggesting multiple introductions into the region and underscoring the diversity of the regional epidemic. We also found that clinically severe cases had genomes belonging to all of these clades. CONCLUSIONS: We established a pipeline for SARS-CoV-2 sequencing within the Johns Hopkins Health system, which enabled us to capture the significant viral diversity present in the region as early as March 2020. Efforts to control local spread of the virus were likely confounded by the number of introductions into the region early in the epidemic and interconnectedness of the region as a whole.

Hematopoietic Stem and Progenitor Cells Exhibit Stage-Specific Translational Programs via mTOR- and CDK1-Dependent Mechanisms.

Hematopoietic stem cells (HSCs) require highly regulated rates of protein synthesis, but it is unclear if they or lineage-committed progenitors preferentially recruit transcripts to translating ribosomes. We utilized polysome profiling, RNA sequencing, and whole-proteomic approaches to examine the translatome in LSK (Lin-Sca-1+c-Kit+) and myeloid progenitor (MP; Lin-Sca-1-c-Kit+) cells. Our studies show that LSKs exhibit low global translation but high translational efficiencies (TEs) of mRNAs required for HSC maintenance. In contrast, MPs activate translation in an mTOR-independent manner due, at least in part, to proteasomal degradation of mTOR by the E3 ubiquitin ligase c-Cbl. In the near absence of mTOR, CDK1 activates eIF4E-dependent translation in MPs through phosphorylation of 4E-BP1. Aberrant activation of mTOR expression and signaling in c-Cbl-deficient MPs results in increased mature myeloid lineage output. Overall, our data demonstrate that hematopoietic stem and progenitor cells (HSPCs) undergo translational reprogramming mediated by previously uncharacterized mechanisms of translational regulation.

The HDAC-Associated Sin3B Protein Represses DREAM Complex Targets and Cooperates with APC/C to Promote Quiescence.

The mammalian DREAM complex is responsible for the transcriptional repression of hundreds of cell-cycle-related genes in quiescence. How the DREAM complex recruits chromatin-modifying entities to aid in its repression remains unknown. Using unbiased proteomics analysis, we have uncovered a robust association between the chromatin-associated Sin3B protein and the DREAM complex. We have determined that genetic inactivation of Sin3B results in the de-repression of DREAM target genes during quiescence but is insufficient to allow quiescent cells to resume proliferation. However, inactivation of APC/CCDH1 was sufficient for Sin3B-/- cells, but not parental cells, to re-enter the cell cycle. These studies identify Sin3B as a transcriptional corepressor associated with the DREAM complex in quiescence and reveals a functional cooperation between E2F target repression and APC/CCDH1 in the negative regulation of cell-cycle progression.

RIVET: comprehensive graphic user interface for analysis and exploration of genome-wide translatomics data.

BACKGROUND: Translatomics data, particularly genome-wide ribosome profiling and polysome profiling, provide multiple levels of gene regulatory information that can be used to assess general transcription and translation, as well translational efficiency. The increasing popularity of these techniques has resulted in multiple algorithms to detect translational regulation, typically distributed in the form of command line tools that require a basic level of programming ability. Additionally, due to the static nature of current software, dynamic transcriptional and translational comparative analysis cannot be adequately achieved. In order to streamline hypothesis generation, investigators must have the ability to manipulate and interact with their data in real-time. RESULTS: To address the lack of integration in current software, we introduce RIVET, Ribosomal Investigation and Visualization to Evaluate Translation, an R shiny based graphical user interface for translatomics data exploration and differential analysis. RIVET can analyze either microarray or RNA sequencing data from polysome profiling and ribosome profiling experiments. RIVET provides multiple choices for statistical analysis as well as integration of transcription, translation, and translational efficiency data analytics and the ability to visualize all results dynamically. CONCLUSIONS: RIVET is a user-friendly tool designed for bench scientists with little to no programming background. RIVET facilitates the data analysis of translatomics data allowing for dynamic generation of results based on user-defined inputs and publication ready visualization. We expect RIVET will allow for scientists to efficiently make more comprehensive data observations that will lead to more robust hypothesis regarding translational regulation.

A genomic ruler to assess oncogenic transition between breast tumor and stroma.

BACKGROUND: Cancers induce gene expression alterations in stroma surrounding tumors that supports cancer progression. However, it is actually not at all known the extent of altered stromal gene expression enacted by tumors nor the extent to which altered stromal gene expression penetrates the stromal tissue. Presently, post-surgical "tumor-free" stromal tissue is determined to be cancer-free based on solely on morphological normality-a criteria that has not changed in more than 100 years despite the existence of sophisticated gene expression data to the contrary. We therefore investigated the extent to which breast tumors alter stromal gene expression in three dimensions in women undergoing mastectomy with the intent of providing a genomic determination for development of future risk of recurrence criteria, and to inform the need for adjuvant full-breast irradiation. METHODS AND FINDINGS: Genome-wide gene expression changes were determined in histopathologically normal breast tissue in 33 women undergoing mastectomy for stage II and III primary invasive ductal carcinoma at serial distances in three dimensions from the tumor. Gene expression was determined by genome-wide mRNA analysis and subjected to metagene mRNA characterization. Tumor-like gene expression signatures in stroma were identified that surprisingly transitioned to a plastic, normalizing homeostatic signature with distance from tumor. Stroma closest to tumor displayed a pronounced tumor-like signature enriched in cancer-promoting pathways involved in disruption of basement membrane, cell migration and invasion, WNT signaling and angiogenesis. By 2 cm from tumor in all dimensions, stromal tissues were in transition, displaying homeostatic and tumor suppressing gene activity, while also expressing cancer supporting pathways. CONCLUSIONS: The dynamics of gene expression in the post-tumor breast stroma likely co-determines disease outcome: reversion to normality or transition to transformation in morphologically normal tissue. Our stromal genomic signature may be important for personalizing surgical and adjuvant therapeutic decisions and risk of recurrence.

mTORC1/2 inhibition re-sensitizes platinum-resistant ovarian cancer by disrupting selective translation of DNA damage and survival mRNAs.

Platinum resistance is a major cause of treatment failure and mortality in epithelial ovarian cancer. mTORC1/2 inhibitors, which impair mRNA translation, can re-sensitize resistant ovarian cancer cells to platinum chemotherapy but the mechanism remains poorly described. Using platinum-resistant OVCAR-3 cells treated with the selective mTORC1/2 inhibitor INK128/MLN128, we conducted genome-wide transcription and translation studies and analyzed the effect on cell proliferation, AKT-mTOR signaling and cell survival, to determine whether carboplatin resistance involves selective mRNA translational reprogramming, and whether it is sensitive to mTORC1/2 inhibition. Gene ontology and Ingenuity Pathway Analysis (IPA) were used to categorize gene expression changes into experimentally authenticated biochemical and molecular networks. We show that carboplatin resistance involves increased mTORC1/2 signaling, resulting in selective translation of mRNAs involved in DNA damage and repair responses (DDR), cell cycle and anti-apoptosis (survival) pathways. Re-sensitization of ovarian cancer cell killing by carboplatin required only modest mTORC1/2 inhibition, with downregulation of protein synthesis by only 20-30%. Genome-wide transcriptomic and translatomic analyses in OVCAR-3 cells revealed that the modest downregulation of global protein synthesis by dual mTORC1/2 inhibition is associated with greater selective inhibition of DDR, cell cycle and survival mRNA translation, which was confirmed in platinum-resistant SKOV-3 cells. These data suggest a clinical path to re-sensitize platinum resistant ovarian cancer to platinum chemotherapy through partial inhibition of mTORC1/2, resulting in selective translation inhibition of DDR and anti-apoptosis protective mRNAs.

A widespread alternate form of cap-dependent mRNA translation initiation.

Translation initiation of most mammalian mRNAs is mediated by a 5' cap structure that binds eukaryotic initiation factor 4E (eIF4E). However, inactivation of eIF4E does not impair translation of many capped mRNAs, suggesting an unknown alternate mechanism may exist for cap-dependent but eIF4E-independent translation. We show that DAP5, an eIF4GI homolog that lacks eIF4E binding, utilizes eIF3d to facilitate cap-dependent translation of approximately 20% of mRNAs. Genome-wide transcriptomic and translatomic analyses indicate that DAP5 is required for translation of many transcription factors and receptor capped mRNAs and their mRNA targets involved in cell survival, motility, DNA repair and translation initiation, among other mRNAs. Mass spectrometry and crosslinking studies demonstrate that eIF3d is a direct binding partner of DAP5. In vitro translation and ribosome complex studies demonstrate that DAP5 and eIF3d are both essential for eIF4E-independent capped-mRNA translation. These studies disclose a widespread and previously unknown mechanism for cap-dependent mRNA translation by DAP5-eIF3d complexes.

Hyperactive mTOR and MNK1 phosphorylation of eIF4E confer tamoxifen resistance and estrogen independence through selective mRNA translation reprogramming.

The majority of breast cancers expresses the estrogen receptor (ER+) and is treated with anti-estrogen therapies, particularly tamoxifen in premenopausal women. However, tamoxifen resistance is responsible for a large proportion of breast cancer deaths. Using small molecule inhibitors, phospho-mimetic proteins, tamoxifen-sensitive and tamoxifen-resistant breast cancer cells, a tamoxifen-resistant patient-derived xenograft model, patient tumor tissues, and genome-wide transcription and translation studies, we show that tamoxifen resistance involves selective mRNA translational reprogramming to an anti-estrogen state by Runx2 and other mRNAs. Tamoxifen-resistant translational reprogramming is shown to be mediated by increased expression of eIF4E and its increased availability by hyperactive mTOR and to require phosphorylation of eIF4E at Ser209 by increased MNK activity. Resensitization to tamoxifen is restored only by reducing eIF4E expression or mTOR activity and also blocking MNK1 phosphorylation of eIF4E. mRNAs specifically translationally up-regulated with tamoxifen resistance include Runx2, which inhibits ER signaling and estrogen responses and promotes breast cancer metastasis. Silencing Runx2 significantly restores tamoxifen sensitivity. Tamoxifen-resistant but not tamoxifen-sensitive patient ER+ breast cancer specimens also demonstrate strongly increased MNK phosphorylation of eIF4E. eIF4E levels, availability, and phosphorylation therefore promote tamoxifen resistance in ER+ breast cancer through selective mRNA translational reprogramming.

Suppression of intestinal tumorigenesis in Apc mutant mice upon Musashi-1 deletion.

Therapeutic strategies based on a specific oncogenic target are better justified when elimination of that particular oncogene reduces tumorigenesis in a model organism. One such oncogene, Musashi-1 (Msi-1), regulates translation of target mRNAs and is implicated in promoting tumorigenesis in the colon and other tissues. Msi-1 targets include the tumor suppressor adenomatous polyposis coli (Apc), a Wnt pathway antagonist lost in ∼80% of all colorectal cancers. Cell culture experiments have established that Msi-1 is a Wnt target, thus positioning Msi-1 and Apc as mutual antagonists in a mutually repressive feedback loop. Here, we report that intestines from mice lacking Msi-1 display aberrant Apc and Msi-1 mutually repressive feedback, reduced Wnt and Notch signaling, decreased proliferation, and changes in stem cell populations, features predicted to suppress tumorigenesis. Indeed, mice with germline Apc mutations (ApcMin ) or with the Apc1322T truncation mutation have a dramatic reduction in intestinal polyp number when Msi-1 is deleted. Taken together, these results provide genetic evidence that Msi-1 contributes to intestinal tumorigenesis driven by Apc loss, and validate the pursuit of Msi-1 inhibitors as chemo-prevention agents to reduce tumor burden.