Mycobacterium abscessus (Mab) is an opportunistic pathogen that can cause chronic, debilitating lung disease. Mab is intrinsically resistant to most antibiotics, making Mab infections challenging to manage and frequently incurable. During infection, Mab adapts to survive various stresses, including hypoxia and nutrient starvation. In vitro, these conditions drive Mab into a drug-tolerant, non-replicating state. Changes in the Mab proteome that result from entering a non-replicating state have been minimally described despite the clinical importance of this physiological state. Using Mab reference strain ATCC 19977, we collected proteomic data comparing replicating to non-replicating states using a carbon starvation (CS) model of persistence. We identified 2251 proteins overall (46% proteome coverage), and 17% of these proteins were found in only one of the two conditions. A third of identified proteins were significantly changed in abundance, indicating an extensive proteomic response to CS. The response regulator DosR and many DosRS responsive proteins were significantly more abundant under CS, suggesting that the DosRS stress response regulator plays a key role in CS-induced Mab persistence. Many aspects of cell wall biosynthesis were changed, including changes in glycolipid abundance under CS. Proteins involved in other key cellular processes such as secretion, oxidative phosphorylation, and nutrient metabolism were altered under CS. The proteomic analysis presented provides new insights and clarity into how the Mab proteome is regulated during non-replicating persistence, a key consideration for understanding Mab pathophysiology.

The pathogen Mycobacterium abscessus ( Mab ) can cause severe and difficult to treat chronic lung infections. Despite the rising incidence and clinical concern of Mab infections, treatment options are limited and often ineffective. Treatment is complicated by Mab ’s ability to persist in a non-replicative, drug-resistant state. Several β-lactam antibiotics are potently bactericidal against Mab but are underutilized because their molecular mechanisms of action against Mab are incompletely understood. In the current study, we used β-lactam-derived activity-based probes and chemoproteomics to report the first comprehensive list of enzymes in Mab targeted by β-lactams. We compared β-lactam targets across two Mab subspecies in actively replicating and non-replicative cultures, using a new carbon starvation model of persistence. We identified 17 targets that were active in every condition tested, seven of which were previously unknown to bind β-lactams. Lastly, we characterized the β-lactamase activity and β-lactam inhibition profiles of nine Mab enzymes, demonstrating that imipenem inhibits these targets more effectively than cefoxitin. These findings provide clarity on the mechanisms of action of clinically relevant β-lactams in Mab , a crucial step toward fully realizing their potential for treating infections caused by this opportunistic pathogen.

Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis (TB), the leading cause of infectious disease-related deaths worldwide. TB infections present on a spectrum from active to latent disease. In the human host, Mtb faces hostile environments, such as nutrient deprivation, hypoxia, and low pH. Under these conditions, Mtb can enter a dormant, but viable, state characterized by a lack of cell replication and increased resistance to antibiotics. Dormant Mtb poses a major challenge to curing infections and eradicating TB globally. We subjected Mtb mc26020 (ΔlysA and ΔpanCD), a double auxotrophic strain, to carbon starvation (CS), a culture condition that induces growth stasis and mimics environmental conditions associated with dormancy in vivo. We provide a detailed analysis of the proteome in CS compared to replicating samples. We observed extensive proteomic reprogramming, with 36% of identified proteins significantly altered in CS. Many enzymes involved in oxidative phosphorylation and lipid metabolism were retained or more abundant in CS. The cell wall biosynthetic machinery was present in CS, although numerous changes in the abundance of peptidoglycan, arabinogalactan, and mycolic acid biosynthetic enzymes likely result in pronounced remodeling of the cell wall. Many clinically approved anti-TB drugs target cell wall biosynthesis, and we found that these enzymes were largely retained in CS. Lastly, we compared our results to those of other dormancy models and propose that CS produces a physiologically distinct state of stasis compared to hypoxia in Mtb.IMPORTANCETuberculosis is a devastating human disease that kills over 1.2 million people a year. This disease is caused by the bacterial pathogen Mycobacterium tuberculosis (Mtb). Mtb excels at surviving in the human host by entering a non-replicating, dormant state. The current work investigated the proteomic changes that Mtb undergoes in response to carbon starvation, a culture condition that models dormancy. The authors found broad effects of carbon starvation on the proteome, with the relative abundance of 37% of proteins significantly altered. Protein changes related to cell wall biosynthesis, metabolism, and drug susceptibility are discussed. Proteins associated with a carbon starvation phenotype are identified, and results are compared to other dormancy models, including hypoxia.

Senescence and the senescence associated secretory phenotype (SASP) are implicated in promoting early tumorigenesis but due to the complexity of SASP it has been difficult to identify the responsible factors. We used canonical SASP factors on our microenvironment microarray (MEMA) platform to systematically identify SASP-associated drivers of tumorigenesis in breast and lung cancer cells. We found multiple SASP factors enhanced the proliferation and overall cell numbers for both lung and breast cells grown on the MEMA, and that there was significant overlap in SASP-associated growth-promoting factors between the two different cell types. We validated the ability of several factors, including IL-6, TGF-β and EGF, to drive growth in in vitro assays. Interestingly, these factors were effective in driving growth and survival in cells that were altered (either immortalized or fully transformed) but not in normal cells and impacted breast cells differently depending on the age of the patient. RNAseq identified upregulation of wound-healing and stem-cell programs in SASP factor-treated cells. Many of these same SASP factors were present in conditioned media collected from senescent cells, which enhanced the growth of both lung and breast cancer cells, and inhibitors of the specific SASP factors partially reduced growth. Similarly, targeted inhibition of EGF partially reduced lung tumour growth in xenografts when senescent but not normal fibroblasts were co-implanted. Our findings have identified core SASP drivers of tumorigenesis and suggest that effective tumorigenesis driven by SASP is multifactorial and requires alterations in the target cells to achieve maximal response.

Infections with Mycobacterium tuberculosis (Mtb) cause tuberculosis (TB), which requires at least 6 months of treatment with multiple antibiotics. There is emergent interest in using β-lactam antibiotics to improve treatment outcomes for patients. These drugs target cell wall biosynthesis, but a comprehensive list of enzymes inhibited by β-lactams in Mtb is lacking. In the current study, we sought to identify and characterize Mtb enzymes inhibited by β-lactam antibiotics using physiological conditions representative of both acute and chronic TB disease. We used new activity-based probes based on the β-lactam antibiotic meropenem due to its approval by the World Health Organization for TB treatment. Activity-based probes label enzymes based on both substrate specificity and catalytic mechanism, enabling precise identification of drug targets. We identified previously undiscovered targets of meropenem in addition to known cell wall biosynthetic enzymes. We validated β-lactam binding and hydrolysis for six newly identified targets: Rv1723, Rv2257c, Rv0309, DapE (Rv1202), MurI (Rv1338), and LipD (Rv1923). Our results demonstrate that there are at least 30 enzymes in Mtb vulnerable to inhibition by meropenem. This is many more β-lactam targets than historically described, suggesting that efficacy in Mtb is a direct result of polypharmacology.

The historical model, which posits that β-lactams inhibit bacterial growth while β-lactamase inhibitors (BLIs) merely protect β-lactams from enzymatic degradation, fails to fully explain their activity against Mycobacterium abscessus (Mab). This study demonstrates that synergistic effects extend beyond the traditional one β-lactam+one BLI paradigm, refuting the oversimplified mechanistic framework. First, β-lactam-based BLIs such as clavulanic acid, sulbactam, and tazobactam exhibit intrinsic antibacterial activity against Mab. These agents synergized not only with β-lactams but also with one another, undermining their historical classification as mere β-lactamase inhibitors. The data indicate that their activity is not limited to inhibiting β-lactamases but extends to directly targeting critical bacterial processes. Second, dual β-lactam combinations exhibit synergism against Mab even in the absence of BLIs. For example, despite being rapidly hydrolyzed by the native β-lactamase BlaMab, amoxicillin demonstrates strong synergism with β-lactams such as imipenem or ceftaroline. This suggests that the second β-lactam either acts as a functional BLI surrogate or targets complementary pathways. Supporting this, experiments using penicillin- and carbapenem-based probes revealed that β-lactams bind to multiple Mab proteins simultaneously, reinforcing the idea that their synergy arises from targeting complementary essential proteins. Finally, triple combinations comprising dual β-lactam and one BLI, such as amoxicillin + ceftaroline + avibactam, achieved very high synergy, underscoring the complementary roles of dual β-lactams and BLIs. The evidence in this study necessitates a revised model that can more accurately explain the activities of β-lactams and BLIs and underscores the potential for optimizing β-lactam/BLI regimens against Mab.

Triple-negative breast cancer (TNBC) shows considerable intratumoral heterogeneity, which contributes to therapeutic resistance. Recent studies show that targeted therapeutics can steer TNBC toward homogeneous, drug-resistant states, but little is understood about how the microenvironment modulates these responses. We report studies to determine how components of the microenvironment impact response to trametinib and cellular heterogeneity. We find that multiple microenvironmental factors, including HGF and neuregulin 1, can drive therapeutic resistance and that treatment with hepatocyte growth factor (HGF) inhibitors restores trametinib sensitivity. Interestingly, treatment with these ligands reverses trametinib-induced homogeneity, restoring heterogeneity to levels comparable to baseline both in vitro and in vivo. Analysis of patient data demonstrates that TNBC with high HGF expression levels has a poor outcome and increased expression of basal and mesenchymal state markers. Our data suggest that common growth factors drive therapeutic resistance and maintain tumor heterogeneity in TNBC, and that co-targeting these factors may improve therapeutic response.

Microenvironment signals are potent determinants of cell fate and arbiters of tissue homeostasis, however understanding how different microenvironment factors coordinately regulate cellular phenotype has been experimentally challenging. Here we used a high-throughput microenvironment microarray comprised of 2640 unique pairwise signals to identify factors that support proliferation and maintenance of primary human mammary luminal epithelial cells. Multiple microenvironment factors that modulated luminal cell number were identified, including: HGF, NRG1, BMP2, CXCL1, TGFB1, FGF2, PDGFB, RANKL, WNT3A, SPP1, HA, VTN, and OMD. All of these factors were previously shown to modulate luminal cell numbers in painstaking mouse genetics experiments, or were shown to have a role in breast cancer, demonstrating the relevance and power of our high-dimensional approach to dissect key microenvironmental signals. RNA-sequencing of primary epithelial and stromal cell lineages identified the cell types that express these signals and the cognate receptors in vivo. Cell-based functional studies confirmed which effects from microenvironment factors were reproducible and robust to individual variation. Hepatocyte growth factor (HGF) was the factor most robust to individual variation and drove expansion of luminal cells via cKit+ progenitor cells, which expressed abundant MET receptor. Luminal cells from women who are genetically high risk for breast cancer had significantly more MET receptor and may explain the characteristic expansion of the luminal lineage in those women. In ensemble, our approach provides proof of principle that microenvironment signals that control specific cellular states can be dissected with high-dimensional cell-based approaches.

Genetic tags aretransformative tools for investigatingthe function,localization, and interactions of cellular proteins. Most studiestoday are reliant on selective labeling of more than one protein toobtain comprehensive information on a protein's behavior insitu. Some proteins can be analyzed by fusion to a protein tag, suchas green fluorescent protein, HaloTag, or SNAP-Tag. Other proteinsbenefit from labeling via small peptide tags, such as the recentlyreported versatile interacting peptide (VIP) tags. VIP tags enableobservations of protein localization and trafficking with bright fluorophoresor nanoparticles. Here, we expand the VIP toolkit by presenting twonew tags: TinyVIPER and PunyVIPER. These two tags were designed foruse with MiniVIPER for labeling up to three distinct proteins at oncein cells. Labeling is mediated by the formation of a high-affinity,biocompatible heterodimeric coiled coil. Each tag was validated byfluorescence microscopy, including observation of transferrin receptor1 trafficking in live cells. We verified that labeling via each tagis highly specific for one- or two-color imaging. Last, the self-sortingtags were used for simultaneous labeling of three protein targets(i.e., TOMM20, histone 2B, and actin) in fixed cells, highlightingtheir utility for multicolor microscopy. MiniVIPER, TinyVIPER, andPunyVIPER are small and robust peptide tags for selective labelingof cellular proteins.

Calorie restriction (CR) inhibits triple-negative breast cancer (TNBC) progression in several preclinical models in association with decreased insulin-like growth factor 1 (IGF1) signaling. To investigate the impact of CR on microRNAs (miRs) that target the IGF1/IGF1R pathway, we used the spontaneous murine model of TNBC, C3(1)/SV40 T-antigen (C3-TAg). In C3-TAg mice, CR reduced body weight, IGF1 levels, and TNBC progression. We evaluated the tumoral expression of 10 miRs. CR increased the expression of miR-199a-3p, miR-199a-5p, miR-486, and miR-15b. However, only miR-15b expression correlated with tumorigenicity in the M28, M6, and M6C C3-TAg cell lines of TNBC progression. Overexpressing miR-15b reduced the proliferation of mouse (M6) and human (MDA-MB-231) cell lines. Serum restriction alone or in combination with low levels of recombinant IGF1 significantly upregulated miR-15b expression and reduced Igf1r in M6 cells. These effects were reversed by the pharmacological inhibition of IGFR with BMS754807. In silico analysis using miR web tools predicted that miR-15b targets genes associated with IGF1/mTOR pathways and the cell cycle. Our findings suggest that CR in association with reduced IGF1 levels could upregulate miR-15b to downregulate Igf1r and contribute to the anticancer effects of CR. Thus, miR-15b may be a therapeutic target for mimicking the beneficial effects of CR against TNBC.

Astrocytes and brain endothelial cells are components of the neurovascular unit that comprises the blood-brain barrier (BBB) and their dysfunction contributes to pathogenesis in Huntington's disease (HD). Defining the contribution of these cells to disease can inform cell-type-specific effects and uncover new disease-modifying therapeutic targets. These cells express integrin (ITG) adhesion receptors that anchor the cells to the extracellular matrix (ECM) to maintain the integrity of the BBB. We used HD patient-derived induced pluripotent stem cell (iPSC) modeling to study the ECM-ITG interface in astrocytes and brain microvascular endothelial cells and found ECM-ITG dysregulation in human iPSC-derived cells that may contribute to the dysfunction of the BBB in HD. This disruption has functional consequences since reducing ITG expression in glia in an HD Drosophila model suppressed disease-associated CNS dysfunction. Since ITGs can be targeted therapeutically and manipulating ITG signaling prevents neurodegeneration in other diseases, defining the role of ITGs in HD may provide a novel strategy of intervention to slow CNS pathophysiology to treat HD.

The phenotype of a cell and its underlying molecular state is strongly influenced by extracellular signals, including growth factors, hormones, and extracellular matrix proteins. While these signals are normally tightly controlled, their dysregulation leads to phenotypic and molecular states associated with diverse diseases. To develop a detailed understanding of the linkage between molecular and phenotypic changes, we generated a comprehensive dataset that catalogs the transcriptional, proteomic, epigenomic and phenotypic responses of MCF10A mammary epithelial cells after exposure to the ligands EGF, HGF, OSM, IFNG, TGFB and BMP2. Systematic assessment of the molecular and cellular phenotypes induced by these ligands comprise the LINCS Microenvironment (ME) perturbation dataset, which has been curated and made publicly available for community-wide analysis and development of novel computational methods ( synapse.org/LINCS_MCF10A ). In illustrative analyses, we demonstrate how this dataset can be used to discover functionally related molecular features linked to specific cellular phenotypes. Beyond these analyses, this dataset will serve as a resource for the broader scientific community to mine for biological insights, to compare signals carried across distinct molecular modalities, and to develop new computational methods for integrative data analysis.

SUMMARYThe phenotype of a cell and its underlying molecular state is strongly influenced by extracellular signals, including growth factors, hormones, and extracellular matrix. While these signals are normally tightly controlled, their dysregulation leads to phenotypic and molecular states associated with diverse diseases. To develop a detailed understanding of the linkage between molecular and phenotypic changes, we generated a comprehensive dataset that catalogs the transcriptional, proteomic, epigenomic and phenotypic responses of MCF10A mammary epithelial cells after exposure to the ligands EGF, HGF, OSM, IFNG, TGFB and BMP2. Systematic assessment of the molecular and cellular phenotypes induced by these ligands comprise the LINCS Microenvironment (ME) perturbation dataset, which has been curated and made publicly available for community-wide analysis and development of novel computational methods (synapse.org/LINCS_MCF10A). In illustrative analyses, we demonstrate how this dataset can be used to discover functionally related molecular features linked to specific cellular phenotypes.

Abstract Background HER2-amplified breast cancer is a clinically defined subtype of breast cancer for which there are multiple viable targeted therapies. Resistance to these targeted therapies is a common problem, but the mechanisms by which resistance occurs remain incompletely defined. One mechanism that has been proposed is through mutation of genes in the PI3-kinase pathway. Intracellular signaling from the HER2 pathway can occur through PI3-kinase, and mutations of the encoding gene PIK3CA are known to be oncogenic. Mutations in PIK3CA co-occur with HER2-amplification in ~ 20% of cases within the HER2-amplified subtype. Methods We generated isogenic knockin mutants of each PIK3CA hotspot mutation in HER2-amplified breast cancer cells using adeno-associated virus-mediated gene targeting. Isogenic clones were analyzed using a combinatorial drug screen to determine differential responses to HER2-targeted therapy. Western blot analysis and immunofluorescence uncovered unique intracellular signaling dynamics in cells resistant to HER2-targeted therapy. Subsequent combinatorial drug screens were used to explore neuregulin-1-mediated resistance to HER2-targeted therapy. Finally, results from in vitro experiments were extrapolated to publicly available datasets. Results Treatment with HER2-targeted therapy reveals that mutations in the kinase domain (H1047R) but not the helical domain (E545K) increase resistance to lapatinib. Mechanistically, sustained AKT signaling drives lapatinib resistance in cells with the kinase domain mutation, as demonstrated by staining for the intracellular product of PI3-kinase, PIP3. This resistance can be overcome by co-treatment with an inhibitor to the downstream kinase AKT. Additionally, knockout of the PIP3 phosphatase, PTEN, phenocopies this result. We also show that neuregulin-1, a ligand for HER-family receptors, confers resistance to cells harboring either hotspot mutation and modulates response to combinatorial therapy. Finally, we show clinical evidence that the hotspot mutations have distinct expression profiles related to therapeutic resistance through analysis of TCGA and METABRIC data cohorts. Conclusion Our results demonstrate unique intracellular signaling differences depending on which mutation in PIK3CA the cell harbors. Only mutations in the kinase domain fully activate the PI3-kinase signaling pathway and maintain downstream signaling in the presence of HER2 inhibition. Moreover, we show there is potentially clinical importance in understanding both the PIK3CA mutational status and levels of neuregulin-1 expression in patients with HER2-amplified breast cancer treated with targeted therapy and that these problems warrant further pre-clinical and clinical testing.

Abstract Calorie restriction (CR) has an antitumorigenic effect against triple-negative breast cancer (TNBC). A key mitogenic pathway modulated by CR involves insulin-like growth factor (IGF)-1, which plays a central role in local and systemic growth and cell survival by activating the PI3K/AKT/mTOR pathway downstream of the IGF-1 receptor (IGF-1R). Although multiple miRNAs that target components of the IGF-1 signaling pathway have been identified, the impact of CR on IGF-1-related miRNA expression has not been addressed. We hypothesize that CR-induced decreases in TNBC development and progression involve miRNA's regulating IGF-1 signaling, we used C3(1)/SV40 T-antigen (C3-TAg) mice (a TNBC model), a C3-Tag progression series of cell lines (M28, M6, and M6C), and human TNBC cell line (MDA-MB-231). The expression of miRNAs previously reported to target components of the IGF-1 and/or mTOR pathways was evaluated by real-time PCR. Hormone levels were measured using the mouse Luminex Screening Assay. To mimic CR in vitro, and to test the effects of miRNA manipulation, the C3-Tag series of TNBC cell lines were treated (separately and in combination) with serum restriction, BMS754807 (inhibitor of IGF1-R), and various levels of recombinant IGF-1 as well as manipulated levels of miRNA's associated with IGF-1/mTOR signaling. We also conducted in silico analysis using Metabric, TCGA, TargetScan, and miRTarBase data sets to identify genes and pathways associated with specific miRNAs expression related to the PI3K/Akt/mTOR pathway. Our results confirm that CR maintains lower body weight, reduces circulating levels of IGF-1, and slows spontaneous TNBC development and progression in mice. CR also significantly increased the expression of miR-15b and miR-486. In vitro studies showed miR-15b and miR-486 expression decreased with increasing tumorigenicity of the C3-tag series of TNBC progression. Treatment of mouse and human TNBC cells with low IGF-1 induced miR-15b expression and inhibited proliferation. Moreover, miR-15b overexpression inhibited cell proliferation and decreased IGF-1R expression (mRNA and protein). Consistent with these results, the in silico analysis shows that the amplification of miR-15b correlates with downregulation of pathways involved in tumor growth and IGF1-R signaling. Together these findings suggest that reduced circulating IGF-1 levels in response to CR leads to the upregulation of miR-15b, which correspondingly targets and downregulates IGF-1R, both at the mRNA and protein levels. This combination of reduced IGF-1 ligand and miR-15b-induced IGF-1R downregulation contributes to the potent anticancer effects of CR and reveals potential targets for pharmacologically mimicking those effects. This research is supported by R35CA197627. Citation Format: Ximena Minerva Bustamante-Marin, Kaylyn L. Devlin, Om Dave, Jenna L. Merlino, Shannon B. McDonell, Michael F. Coleman, Stephen D. Hursting. Anticancer effects of calorie restriction in a murine C3-TAg model of triple-negative breast cancer: the role of miR-15b [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2357.

Triple negative breast cancer (TNBC) lacks expression of hormone receptors (ER and PR) and HER2 and is characterized by aggressive disease with poor outcomes. Recent work suggests that TNBC also has a high degree of intratumoral heterogeneity, as measured by lineage differentiation status. This heterogeneity may impact therapeutic response, as it has been shown that treatment with PI3K/mTOR (BEZ235) or MEK (trametinib) inhibitors can drive TNBC cells into more homogeneous states, but that the surviving cells are resistant to the targeted therapy. In this study, we sought to understand how the microenvironment impacts differentiation state heterogeneity and response to targeted therapeutics in HCC1143 cells using our microenvironment microarray (MEMA) platform. Under low serum growth conditions, we found that several ligands could drive the growth of HCC1143, particularly EGF family ligands like AREG and EGF. With respect to differentiation state and heterogeneity, EGF and TGFB1 drove HCC1143 cells into a more mesenchymal like state, with increased expression of VIM and decreased expression of KRT14. In contrast, BMP2 led to higher levels of KRT14 and lower levels of VIM, leading to a more basal-like state. We also grew HCC1143 on MEMA with trametinib treatment. Here we found that combinations of collagen-based substrates and NRG1, HGF, and EGF ligands all led to higher cell counts and EdU incorporation rates compared to PBS-control treated cells. However, the levels of resistance conferred by the microenvironment was less than we had previously seen in HER2 positive MEMA, as the GR50 values (dose required to inhibit growth by 50%) only increased modestly (18 nM for untreated cells, 40 nM for NRG1, 45 nM for HGF). Interestingly, in that HER2 positive MEMA study, we identified HGF and NRG1 as potent resistance factors to lapatinib, but that they functioned in a subtype specific manner. HGF was effective in basal subtype cells and NRG1 in luminal, but not vice versa. We postulated that the modest resistance we observed was due to ligands acting on subsets of cells. We thus treated cells with a combination of NRG1 plus HGF, and found that this resulted in increased resistance (GR50= 91 nM). Imaging showed that trametinib drove HCC1143 cells to a homogenous KRT14 positive state, but surprisingly, addition of ligands reverted the cells to a more heterogeneous state that was resistant to trametinib. These data demonstrate that the microenvironment can impact the differentiation state of TNBC cells and is also capable of conferring resistance within subsets of the heterogeneous cell populations. Citation Format: Rebecca Smith, Kaylyn Devlin, Moqing Liu, Tiera Liby, David Kilburn, Elmar Bucher, Damir Sudar, Guillaume Thibault, Mark Dane, Joe Gray, Laura Heiser, James E. Korkola. The impact of the microenvironment on heterogeneity and trametinib response in HCC1143 triple negative breast cancer cells [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1870.

The scaffold protein Tks5α is required for invadopodia-mediated cancer invasion both in vitro and in vivo. We have previously also revealed a role for Tks5 in tumor cell growth using three-dimensional (3D) culture model systems and mouse transplantation experiments. Here we use both 3D and high-density fibrillar collagen (HDFC) culture to demonstrate that native collagen-I, but not a form lacking the telopeptides, stimulated Tks5-dependent growth, which was dependent on the DDR collagen receptors. We used microenvironmental microarray (MEMA) technology to determine that laminin, fibronectin and tropoelastin also stimulated invadopodia formation. A Tks5α-specific monoclonal antibody revealed its expression both on microtubules and at invadopodia. High- and super-resolution microscopy of cells in and on collagen was then used to place Tks5α at the base of invadopodia, separated from much of the actin and cortactin, but coincident with both matrix metalloprotease and cathepsin proteolytic activity. Inhibition of the Src family kinases, cathepsins or metalloproteases all reduced invadopodia length but each had distinct effects on Tks5α localization. These studies highlight the crosstalk between invadopodia and extracellular matrix components, and reveal the invadopodium to be a spatially complex structure.

Background In biological experiments, comprehensive experimental metadata tracking – which comprises experiment, reagent, and protocol annotation with controlled vocabulary from established ontologies – remains a challenge, especially when the experiment involves multiple laboratory scientists who execute different steps of the protocol. Here we describe Annot, a novel web application designed to provide a flexible solution for this task. Results Annot enforces the use of controlled vocabulary for sample and reagent annotation while enabling robust investigation, study, and protocol tracking. The cornerstone of Annot’s implementation is a json syntax-compatible file format, which can capture detailed metadata for all aspects of complex biological experiments. Data stored in this json file format can easily be ported into spreadsheet or data frame files that can be loaded into R ( https://www.r-project.org/ ) or Pandas, Python’s data analysis library ( https://pandas.pydata.org/ ). Annot is implemented in Python3 and utilizes the Django web framework, Postgresql, Nginx, and Debian. It is deployed via Docker and supports all major browsers. Conclusions Annot offers a robust solution to annotate samples, reagents, and experimental protocols for established assays where multiple laboratory scientists are involved. Further, it provides a framework to store and retrieve metadata for data analysis and integration, and therefore ensures that data generated in different experiments can be integrated and jointly analyzed. This type of solution to metadata tracking can enhance the utility of large-scale datasets, which we demonstrate here with a large-scale microenvironment microarray study.

Understanding the impact of the microenvironment on the phenotype of cells is a difficult problem due to the complex mixture of both soluble growth factors and matrix-associated proteins in the microenvironment in vivo. Furthermore, readily available reagents for the modeling of microenvironments in vitro typically utilize complex mixtures of proteins that are incompletely defined and suffer from batch to batch variability. The microenvironment microarray (MEMA) platform allows for the assessment of thousands of simple combinations of microenvironment proteins for their impact on cellular phenotypes in a single assay. The MEMAs are prepared in well plates, which allows the addition of individual ligands to separate wells containing arrayed extracellular matrix (ECM) proteins. The combination of the soluble ligand with each printed ECM forms a unique combination. A typical MEMA assay contains greater than 2,500 unique combinatorial microenvironments that cells are exposed to in a single assay. As a test case, the breast cancer cell line MCF7 was plated on the MEMA platform. Analysis of this assay identified factors that both enhance and inhibit the growth and proliferation of these cells. The MEMA platform is highly flexible and can be extended for use with other biological questions beyond cancer research.

The Library of Integrated Network-Based Cellular Signatures (LINCS) is an NIH Common Fund program that catalogs how human cells globally respond to chemical, genetic, and disease perturbations. Resources generated by LINCS include experimental and computational methods, visualization tools, molecular and imaging data, and signatures. By assembling an integrated picture of the range of responses of human cells exposed to many perturbations, the LINCS program aims to better understand human disease and to advance the development of new therapies. Perturbations under study include drugs, genetic perturbations, tissue micro-environments, antibodies, and disease-causing mutations. Responses to perturbations are measured by transcript profiling, mass spectrometry, cell imaging, and biochemical methods, among other assays. The LINCS program focuses on cellular physiology shared among tissues and cell types relevant to an array of diseases, including cancer, heart disease, and neurodegenerative disorders. This Perspective describes LINCS technologies, datasets, tools, and approaches to data accessibility and reusability.