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Identifying genetic biomarkers of patient survival remains a major goal of large-scale cancer profiling studies. Using gene expression data to predict the outcome of a patient's tumor makes biomarker discovery a compelling tool for improving patient care. As genomic technologies expand, multiple data types may serve as informative biomarkers, and bioinformatic strategies have evolved around these different applications. For categorical variables such as a gene's mutation status, biomarker identification to predict survival time is straightforward. However, for continuous variables like gene expression, the available methods generate highly-variable results, and studies on best practices are lacking. We investigated the performance of eight methods that deal specifically with continuous data. K-means, Cox regression, concordance index, D-index, 25th-75th percentile split, median-split, distribution-based splitting, and KaplanScan were applied to four RNA-sequencing (RNA-seq) datasets from the Cancer Genome Atlas. The reliability of the eight methods was assessed by splitting each dataset into two groups and comparing the overlap of the results. Gene sets that had been identified from the literature for a specific tumor type served as positive controls to assess the accuracy of each biomarker using receiver operating characteristic (ROC) curves. Artificial RNA-Seq data were generated to test the robustness of these methods under fixed levels of gene expression noise. Our results show that methods based on dichotomizing tend to have consistently poor performance while C-index, D-index, and k-means perform well in most settings. Overall, the Cox regression method had the strongest performance based on tests of accuracy, reliability, and robustness., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Lysine methylation of histones and non-histone substrates by the SET domain containing protein lysine methyltransferase (KMT) G9a/EHMT2 governs transcription contributing to apoptosis, aberrant cell growth, and pluripotency. The positioning of chromosomes within the nuclear three-dimensional space involves interactions between nuclear lamina (NL) and the lamina-associated domains (LAD). Contact of individual LADs with the NL are dependent upon H3K9me2 introduced by G9a. The mechanisms governing the recruitment of G9a to distinct subcellular sites, into chromatin or to LAD, is not known. The cyclin D1 gene product encodes the regulatory subunit of the holoenzyme that phosphorylates pRB and NRF1 thereby governing cell-cycle progression and mitochondrial metabolism. Herein, we show that cyclin D1 enhanced H3K9 dimethylation though direct association with G9a. Endogenous cyclin D1 was required for the recruitment of G9a to target genes in chromatin, for G9a-induced H3K9me2 of histones, and for NL-LAD interaction. The finding that cyclin D1 is required for recruitment of G9a to target genes in chromatin and for H3K9 dimethylation, identifies a novel mechanism coordinating protein methylation.

Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer death in the US. Despite multiple large-scale genetic sequencing studies, identification of predictors of patient survival remains challenging. We performed a comprehensive assessment and integrative analysis of large-scale gene expression datasets, across multiple platforms, to enable discovery of a prognostic gene signature for patient survival in pancreatic cancer. PDAC RNA-Sequencing data from The Cancer Genome Atlas was stratified into Survival+ (>2-year survival) and Survival-(<1-year survival) cohorts (n = 47). Comparisons of RNA expression profiles between survival groups and normal pancreatic tissue expression data from the Gene Expression Omnibus generated an initial PDAC specific prognostic differential expression gene list. The candidate prognostic gene list was then trained on the Australian pancreatic cancer dataset from the ICGC database (n = 103), using iterative sampling based algorithms, to derive a gene signature predictive of patient survival. The gene signature was validated in 2 independent patient cohorts and against existing PDAC subtype classifications. We identified 707 candidate prognostic genes exhibiting differential expression in tumor versus normal tissue. A substantial fraction of these genes was also found to be differentially methylated between survival groups. From the candidate gene list, a 5-gene signature (ADM, ASPM, DCBLD2, E2F7, and KRT6A) was identified. Our signature demonstrated significant power to predict patient survival in two distinct patient cohorts and was independent of AJCC TNM staging. Cross-validation of our gene signature reported a better ROC AUC (≥ 0.8) when compared to existing PDAC survival signatures. Furthermore, validation of our signature through immunohistochemical analysis of patient tumor tissue and existing gene expression subtyping data in PDAC, demonstrated a correlation to the presence of vascular invasion and the aggressive squamous tumor subtype. Assessment of these genes in patient biopsies could help further inform risk-stratification and treatment decisions in pancreatic cancer., Competing Interests: The authors have declared that no competing interests exist. While K.H.L is currently employed by Stoke Therapeutics, his contributions occurred entirely during his time at Drexel University. This does not alter the authors' adherence to PLOS ONE policies on sharing data and materials.

Background: Genetic classification of breast cancer based on the coding mRNA suggests the evolution of distinct subtypes. Whether the non-coding genome is altered concordantly with the coding genome and the mechanism by which the cell cycle directly controls the non-coding genome is poorly understood. Methods: Herein, the miRNA signature maintained by endogenous cyclin D1 in human breast cancer cells was defined. In order to determine the clinical significance of the cyclin D1-mediated miRNA signature, we defined a miRNA expression superset from 459 breast cancer samples. We compared the coding and non-coding genome of breast cancer subtypes. Results: Hierarchical clustering of human breast cancers defined four distinct miRNA clusters (G1-G4) associated with distinguishable relapse-free survival by Kaplan-Meier analysis. The cyclin D1-regulated miRNA signature included several oncomirs, was conserved in multiple breast cancer cell lines, was associated with the G2 tumor miRNA cluster, ERα + status, better outcome and activation of the Wnt pathway. The coding and non-coding genome were discordant within breast cancer subtypes. Seed elements for cyclin D1-regulated miRNA were identified in 63 genes of the Wnt signaling pathway including DKK. Cyclin D1 restrained DKK1 via the 3'UTR. In vivo studies using inducible transgenics confirmed cyclin D1 induces Wnt-dependent gene expression. Conclusion: The non-coding genome defines breast cancer subtypes that are discordant with their coding genome subtype suggesting distinct evolutionary drivers within the tumors. Cyclin D1 orchestrates expression of a miRNA signature that induces Wnt/ β -catenin signaling, therefore cyclin D1 serves both upstream and downstream of Wnt/ β -catenin signaling., Competing Interests: Competing Interests: The authors have declared that no competing interest exists.

Background: Bacterial infections comprise a global health challenge as the incidences of antibiotic resistance increase. Pathogenic potential of bacteria has been shown to be context dependent, varying in response to environment and even within the strains of the same genus., Results: We used the KEGG repository and extensive literature searches to identify among the 2527 bacterial genomes in the literature those implicated as pathogenic to the host, including those which show pathogenicity in a context dependent manner. Using data on the gene contents of these genomes, we identified sets of genes highly abundant in pathogenic but relatively absent in commensal strains and vice versa. In addition, we carried out genome comparison within a genus for the seventeen largest genera in our genome collection. We projected the resultant lists of ortholog genes onto KEGG bacterial pathways to identify clusters and circuits, which can be linked to either pathogenicity or synergy. Gene circuits relatively abundant in nonpathogenic bacteria often mediated biosynthesis of antibiotics. Other synergy-linked circuits reduced drug-induced toxicity. Pathogen-abundant gene circuits included modules in one-carbon folate, two-component system, type-3 secretion system, and peptidoglycan biosynthesis. Antibiotics-resistant bacterial strains possessed genes modulating phagocytosis, vesicle trafficking, cytoskeletal reorganization, and regulation of the inflammatory response. Our study also identified bacterial genera containing a circuit, elements of which were previously linked to Alzheimer's disease., Conclusions: Present study produces for the first time, a signature, in the form of a robust list of gene circuitry whose presence or absence could potentially define the pathogenicity of a microbiome. Extensive literature search substantiated a bulk majority of the commensal and pathogenic circuitry in our predicted list. Scanning microbiome libraries for these circuitry motifs will provide further insights into the complex and context dependent pathogenicity of bacteria.

Ovarian cancer (OC) is a leading cause of cancer mortality, but aside from a few well-studied mutations, very little is known about its underlying causes. As such, we performed survival analysis on ovarian copy number amplifications and gene expression datasets presented by The Cancer Genome Atlas in order to identify potential drivers and markers of aggressive OC. Additionally, two independent datasets from the Gene Expression Omnibus web platform were used to validate the identified markers. Based on our analysis, we identified FXYD5, a glycoprotein known to reduce cell adhesion, as a potential driver of metastasis and a significant predictor of mortality in OC. As a marker of poor outcome, the protein has effective antibodies against it for use in tissue arrays. FXYD5 bridges together a wide variety of cancers, including ovarian, breast cancer stage II, thyroid, colorectal, pancreatic, and head and neck cancers for metastasis studies.

Cyclin D1 is an important molecular driver of human breast cancer but better understanding of its oncogenic mechanisms is needed, especially to enhance efforts in targeted therapeutics. Currently, pharmaceutical initiatives to inhibit cyclin D1 are focused on the catalytic component since the transforming capacity is thought to reside in the cyclin D1/CDK activity. We initiated the following study to directly test the oncogenic potential of catalytically inactive cyclin D1 in an in vivo mouse model that is relevant to breast cancer. Herein, transduction of cyclin D1(-/-) mouse embryonic fibroblasts (MEFs) with the kinase dead KE mutant of cyclin D1 led to aneuploidy, abnormalities in mitotic spindle formation, autosome amplification, and chromosomal instability (CIN) by gene expression profiling. Acute transgenic expression of either cyclin D1(WT) or cyclin D1(KE) in the mammary gland was sufficient to induce a high CIN score within 7 days. Sustained expression of cyclin D1(KE) induced mammary adenocarcinoma with similar kinetics to that of the wild-type cyclin D1. ChIP-Seq studies demonstrated recruitment of cyclin D1(WT) and cyclin D1(KE) to the genes governing CIN. We conclude that the CDK-activating function of cyclin D1 is not necessary to induce either chromosomal instability or mammary tumorigenesis.

Hyperactive EGF receptor (EGFR) and mutant p53 are common genetic abnormalities driving the progression of non-small cell lung cancer (NSCLC), the leading cause of cancer deaths in the world. The Drosophila gene Dachshund (Dac) was originally cloned as an inhibitor of hyperactive EGFR alleles. Given the importance of EGFR signaling in lung cancer etiology, we examined the role of DACH1 expression in lung cancer development. DACH1 protein and mRNA expression was reduced in human NSCLC. Reexpression of DACH1 reduced NSCLC colony formation and tumor growth in vivo via p53. Endogenous DACH1 colocalized with p53 in a nuclear, extranucleolar location, and shared occupancy of -15% of p53-bound genes in ChIP sequencing. The C-terminus of DACH1 was necessary for direct p53 binding, contributing to the inhibition of colony formation and cell-cycle arrest. Expression of the stem cell factor SOX2 was repressed by DACH1, and SOX2 expression was inversely correlated with DACH1 in NSCLC. We conclude that DACH1 binds p53 to inhibit NSCLC cellular growth., (©2013 AACR.)

Cyclin D1 encodes the regulatory subunit of a holoenzyme that phosphorylates the pRB protein and promotes G1/S cell-cycle progression and oncogenesis. Dicer is a central regulator of miRNA maturation, encoding an enzyme that cleaves double-stranded RNA or stem-loop-stem RNA into 20-25 nucleotide long small RNA, governing sequence-specific gene silencing and heterochromatin methylation. The mechanism by which the cell cycle directly controls the non-coding genome is poorly understood. Here we show that cyclin D1(-/-) cells are defective in pre-miRNA processing which is restored by cyclin D1a rescue. Cyclin D1 induces Dicer expression in vitro and in vivo. Dicer is transcriptionally targeted by cyclin D1, via a cdk-independent mechanism. Cyclin D1 and Dicer expression significantly correlates in luminal A and basal-like subtypes of human breast cancer. Cyclin D1 and Dicer maintain heterochromatic histone modification (Tri-m-H3K9). Cyclin D1-mediated cellular proliferation and migration is Dicer-dependent. We conclude that cyclin D1 induction of Dicer coordinates microRNA biogenesis.

Background: Inflammatory bowel disease (IBD) is a complex disorder involving pathogen infection, host immune response, and altered enterocyte physiology. Incidences of IBD are increasing at an alarming rate in developed countries, warranting a detailed molecular portrait of IBD., Methods: We used large-scale data, bioinformatics tools, and high-throughput computations to obtain gene and microRNA signatures for Crohn's disease (CD) and ulcerative colitis (UC). These signatures were then integrated with systemic literature review to draw a comprehensive portrait of IBD in relation to autoimmune diseases., Results: The top upregulated genes in IBD are associated with diabetogenesis (REG1A, REG1B), bacterial signals (TLRs, NLRs), innate immunity (DEFA6, IDO1, EXOSC1), inflammation (CXCLs), and matrix degradation (MMPs). The downregulated genes coded tight junction proteins (CLDN8), solute transporters (SLCs), and adhesion proteins. Genes highly expressed in UC compared to CD included antiinflammatory ANXA1, transporter ABCA12, T-cell activator HSH2D, and immunoglobulin IGHV4-34. Compromised metabolisms for processing of drugs, nitrogen, androgen and estrogen, and lipids in IBD correlated with an increase in specific microRNA. Highly expressed IBD genes constituted targets of drugs used in gastrointestinal cancers, viral infections, and autoimmunity disorders such as rheumatoid arthritis and asthma., Conclusions: This study presents a clinically relevant gene-level portrait of IBD subtypes and their connectivity to autoimmune diseases. The study identified candidates for repositioning of existing drugs to manage IBD. Integration of mice and human data point to an altered B-cell response as a cause for upregulation of genes in IBD involved in other aspects of immune defense such as interferon-inducible responses., (Copyright © 2012 Crohn's & Colitis Foundation of America, Inc.)

Chromosomal instability (CIN) in tumors is characterized by chromosomal abnormalities and an altered gene expression signature; however, the mechanism of CIN is poorly understood. CCND1 (which encodes cyclin D1) is overexpressed in human malignancies and has been shown to play a direct role in transcriptional regulation. Here, we used genome-wide ChIP sequencing and found that the DNA-bound form of cyclin D1 occupied the regulatory region of genes governing chromosomal integrity and mitochondrial biogenesis. Adding cyclin D1 back to Ccnd1(-/-) mouse embryonic fibroblasts resulted in CIN gene regulatory region occupancy by the DNA-bound form of cyclin D1 and induction of CIN gene expression. Furthermore, increased chromosomal aberrations, aneuploidy, and centrosome abnormalities were observed in the cyclin D1-rescued cells by spectral karyotyping and immunofluorescence. To assess cyclin D1 effects in vivo, we generated transgenic mice with acute and continuous mammary gland-targeted cyclin D1 expression. These transgenic mice presented with increased tumor prevalence and signature CIN gene profiles. Additionally, interrogation of gene expression from 2,254 human breast tumors revealed that cyclin D1 expression correlated with CIN in luminal B breast cancer. These data suggest that cyclin D1 contributes to CIN and tumorigenesis by directly regulating a transcriptional program that governs chromosomal stability.

Background: Pandemic and seasonal respiratory viruses are a major global health concern. Given the genetic diversity of respiratory viruses and the emergence of drug resistant strains, the targeted disruption of human host-virus interactions is a potential therapeutic strategy for treating multi-viral infections. The availability of large-scale genomic datasets focused on host-pathogen interactions can be used to discover novel drug targets as well as potential opportunities for drug repositioning., Methods/results: In this study, we performed a large-scale analysis of microarray datasets involving host response to infections by influenza A virus, respiratory syncytial virus, rhinovirus, SARS-coronavirus, metapneumonia virus, coxsackievirus and cytomegalovirus. Common genes and pathways were found through a rigorous, iterative analysis pipeline where relevant host mRNA expression datasets were identified, analyzed for quality and gene differential expression, then mapped to pathways for enrichment analysis. Possible repurposed drugs targets were found through database and literature searches. A total of 67 common biological pathways were identified among the seven different respiratory viruses analyzed, representing fifteen laboratories, nine different cell types, and seven different array platforms. A large overlap in the general immune response was observed among the top twenty of these 67 pathways, adding validation to our analysis strategy. Of the top five pathways, we found 53 differentially expressed genes affected by at least five of the seven viruses. We suggest five new therapeutic indications for existing small molecules or biological agents targeting proteins encoded by the genes F3, IL1B, TNF, CASP1 and MMP9. Pathway enrichment analysis also identified a potential novel host response, the Parkin-Ubiquitin Proteasomal System (Parkin-UPS) pathway, which is known to be involved in the progression of neurodegenerative Parkinson's disease., Conclusions: Our study suggests that multiple and diverse respiratory viruses invoke several common host response pathways. Further analysis of these pathways suggests potential opportunities for therapeutic intervention.

The global gene expression analysis of cancer and healthy tissues typically results in large numbers of genes that are significantly altered in cancer. Such data, however, has been difficult to interpret due to the high level of variation of gene lists across laboratories and the small sample sizes used in individual studies. In this investigation, we compiled microarray data obtained from the same platform family from 84 laboratories, resulting in a database containing 1,043 healthy tissue samples and 4,900 cancer samples for 13 different tissue types. The primary cancers considered included adrenal gland, brain, breast, cervix, colon, kidney, liver, lung, ovary, pancreas, prostate and skin tissues. We normalized the data together and analyzed subsets for the discovery of genes involved in normal to cancer transformation. Our integrated significance analysis of microarrays approach produced top 400 gene lists for each of the 13 cancer types. These lists were highly statistically enriched with genes already associated with cancer in research publications excluding microarray studies (p < 1.31 E - 12). The genes MTIM and RRM2 appeared in nine and TOP2A in eight lists of significantly altered genes in cancer. In total, there were 132 genes present in at least four gene lists, 11 of which were not previously associated with cancer. The list contains 17 metal ions and 15 adenyl ribonucleotide binding proteins, six kinases and six transcription factors. Our results point to the value of integrating microarray data in the study of combination drug therapies targeting metastasis., (Copyright © 2010 UICC.)

HIV proteins target host hub proteins for transient binding interactions. The presence of viral proteins in the infected cell results in out-competition of host proteins in their interaction with hub proteins, drastically affecting cell physiology. Functional genomics and interactome datasets can be used to quantify the sequence hotspots on the HIV proteome mediating interactions with host hub proteins. In this study, we used the HIV and human interactome databases to identify HIV targeted host hub proteins and their host binding partners (H2). We developed a high throughput computational procedure utilizing motif discovery algorithms on sets of protein sequences, including sequences of HIV and H2 proteins. We identified as HIV sequence hotspots those linear motifs that are highly conserved on HIV sequences and at the same time have a statistically enriched presence on the sequences of H2 proteins. The HIV protein motifs discovered in this study are expressed by subsets of H2 host proteins potentially outcompeted by HIV proteins. A large subset of these motifs is involved in cleavage, nuclear localization, phosphorylation, and transcription factor binding events. Many such motifs are clustered on an HIV sequence in the form of hotspots. The sequential positions of these hotspots are consistent with the curated literature on phenotype altering residue mutations, as well as with existing binding site data. The hotspot map produced in this study is the first global portrayal of HIV motifs involved in altering the host protein network at highly connected hub nodes.

Virus proteins alter protein pathways of the host toward the synthesis of viral particles by breaking and making edges via binding to host proteins. In this study, we developed a computational approach to predict viral sequence hotspots for binding to host proteins based on sequences of viral and host proteins and literature-curated virus-host protein interactome data. We use a motif discovery algorithm repeatedly on collections of sequences of viral proteins and immediate binding partners of their host targets and choose only those motifs that are conserved on viral sequences and highly statistically enriched among binding partners of virus protein targeted host proteins. Our results match experimental data on binding sites of Nef to host proteins such as MAPK1, VAV1, LCK, HCK, HLA-A, CD4, FYN, and GNB2L1 with high statistical significance but is a poor predictor of Nef binding sites on highly flexible, hoop-like regions. Predicted hotspots recapture CD8 cell epitopes of HIV Nef highlighting their importance in modulating virus-host interactions. Host proteins potentially targeted or outcompeted by Nef appear crowding the T cell receptor, natural killer cell mediated cytotoxicity, and neurotrophin signaling pathways. Scanning of HIV Nef motifs on multiple alignments of hepatitis C protein NS5A produces results consistent with literature, indicating the potential value of the hotspot discovery in advancing our understanding of virus-host crosstalk.

Background: Much of the public access cancer microarray data is asymmetric, belonging to datasets containing no samples from normal tissue. Asymmetric data cannot be used in standard meta-analysis approaches (such as the inverse variance method) to obtain large sample sizes for statistical power enrichment. Noting that plenty of normal tissue microarray samples exist in studies not involving cancer, we investigated the viability and accuracy of an integrated microarray analysis approach based on significance analysis of microarrays (merged SAM) using a collection of data from separate diseased and normal samples., Results: We focused on five solid cancer types (colon, kidney, liver, lung, and pancreas), where available microarray data allowed us to compare meta-analysis and integrated approaches. Our results from the merged SAM significantly overlapped gene lists from the validated inverse-variance method. Both meta-analysis and merged SAM approaches successfully captured the aberrances in the cell cycle that commonly occur in the different cancer types. However, the integrated SAM analysis replicated the known cancer literature (excluding microarray studies) with much more accuracy than the meta-analysis., Conclusion: The merged SAM test is a powerful, robust approach for combining data from similar platforms and for analyzing asymmetric datasets, including those with only normal or only cancer samples that cannot be utilized by meta-analysis methods. The integrated SAM approach can also be used in comparing global gene expression between various subtypes of cancer arising from the same tissue.

Single nucleotide polymorphisms (SNPs) constitute an important mode of genetic variations observed in the human genome. A small fraction of SNPs, about four thousand out of the ten million, has been associated with genetic disorders and complex diseases. The present study focuses on SNPs that fall on protein domains, 3D structures that facilitate connectivity of proteins in cell signaling and metabolic pathways. We scanned the human proteome using the PROSITE web tool and identified proteins with SNP containing domains. We showed that SNPs that fall on protein domains are highly statistically enriched among SNPs linked to hereditary disorders and complex diseases. Proteins whose domains are dramatically altered by the presence of an SNP are even more likely to be present among proteins linked to hereditary disorders. Proteins with domain-altering SNPs comprise highly connected nodes in cellular pathways such as the focal adhesion, the axon guidance pathway and the autoimmune disease pathways. Statistical enrichment of domain/motif signatures in interacting protein pairs indicates extensive loss of connectivity of cell signaling pathways due to domain-altering SNPs, potentially leading to hereditary disorders.

Background: Phosphorylation events direct the flow of signals and metabolites along cellular protein networks. Current annotations of kinase-substrate binding events are far from complete. In this study, we scanned the entire human protein sequences using the PROSITE domain annotation tool to identify patterns of domain composition in kinases and their substrates. We identified statistically enriched pairs of strings of domains (signature pairs) in kinase-substrate couples presented in the 2006 version of the PTM database., Results: The signature pairs enriched in kinase - substrate binding interactions turned out to be highly specific to kinase subtypes. The resulting list of signature pairs predicted kinase-substrate interactions in validation dataset not used in learning with high statistical accuracy., Conclusions: The method presented here produces predictions of protein phosphorylation events with high accuracy and mid-level coverage. Our method can be used in expanding the currently available drafts of cell signaling pathways and thus will be an important tool in the development of combination drug therapies targeting complex diseases.

The Drosophila Dachshund (Dac) gene, cloned as a dominant inhibitor of the hyperactive growth factor mutant ellipse, encodes a key component of the retinal determination gene network that governs cell fate. Herein, cyclic amplification and selection of targets identified a DACH1 DNA-binding sequence that resembles the FOX (Forkhead box-containing protein) binding site. Genome-wide in silico promoter analysis of DACH1 binding sites identified gene clusters populating cellular pathways associated with the cell cycle and growth factor signaling. ChIP coupled with high-throughput sequencing mapped DACH1 binding sites to corresponding gene clusters predicted in silico and identified as weight matrix resembling the cyclic amplification and selection of targets-defined sequence. DACH1 antagonized FOXM1 target gene expression, promoter occupancy in the context of local chromatin, and contact-independent growth. Attenuation of FOX function by the cell fate determination pathway has broad implications given the diverse role of FOX proteins in cellular biology and tumorigenesis.

Over the course of HIV infection, virus replication is facilitated by the phosphorylation of HIV proteins by human ERK1 and ERK2 mitogen-activated protein kinases (MAPKs). MAPKs are known to phosphorylate their substrates by first binding with them at a docking site. Docking site interactions could be viable drug targets because the sequences guiding them are more specific than phosphorylation consensus sites. In this study we use multiple bioinformatics tools to discover candidate MAPK docking site motifs on HIV proteins known to be phosphorylated by MAPKs, and we discuss the possibility of targeting docking sites with drugs. Using sequence alignments of HIV proteins of different subtypes, we show that MAPK docking patterns previously described for human proteins appear on the HIV matrix, Tat, and Vif proteins in a strain dependent manner, but are absent from HIV Rev and appear on all HIV Nef strains. We revise the regular expressions of previously annotated MAPK docking patterns in order to provide a subtype independent motif that annotates all HIV proteins. One revision is based on a documented human variant of one of the substrate docking motifs, and the other reduces the number of required basic amino acids in the standard docking motifs from two to one. The proposed patterns are shown to be consistent with in silico docking between ERK1 and the HIV matrix protein. The motif usage on HIV proteins is sufficiently different from human proteins in amino acid sequence similarity to allow for HIV specific targeting using small-molecule drugs.

Background: The HIV viral genome mutates at a high rate and poses a significant long term health risk even in the presence of combination antiretroviral therapy. Current methods for predicting a patient's response to therapy rely on site-directed mutagenesis experiments and in vitro resistance assays. In this bioinformatics study we treat response to antiretroviral therapy as a two-body problem: response to therapy is considered to be a function of both the host and pathogen proteomes. We set out to identify potential responders based on the presence or absence of host protein and DNA motifs on the HIV proteome., Results: An alignment of thousands of HIV-1 sequences attested to extensive variation in nucleotide sequence but also showed conservation of eukaryotic short linear motifs on the protein coding regions. The reduction in viral load of patients in the Stanford HIV Drug Resistance Database exhibited a bimodal distribution after 24 weeks of antiretroviral therapy, with 2,000 copies/ml cutoff. Similarly, patients allocated into responder/non-responder categories based on consistent viral load reduction during a 24 week period showed clear separation. In both cases of phenotype identification, a set of features composed of short linear motifs in the reverse transcriptase region of HIV sequence accurately predicted a patient's response to therapy. Motifs that overlap resistance sites were highly predictive of responder identification in single drug regimens but these features lost importance in defining responders in multi-drug therapies., Conclusion: HIV sequence mutates in a way that preferentially preserves peptide sequence motifs that are also found in the human proteome. The presence and absence of such motifs at specific regions of the HIV sequence is highly predictive of response to therapy. Some of these predictive motifs overlap with known HIV-1 resistance sites. These motifs are well established in bioinformatics databases and hence do not require identification via in vitro mutation experiments.

Background: Host protein-protein interaction networks are altered by invading virus proteins, which create new interactions, and modify or destroy others. The resulting network topology favors excessive amounts of virus production in a stressed host cell network. Short linear peptide motifs common to both virus and host provide the basis for host network modification., Methods: We focused our host-pathogen study on the binding and competing interactions of HIV-1 and human proteins. We showed that peptide motifs conserved across 70% of HIV-1 subtype B and C samples occurred in similar positions on HIV-1 proteins, and we documented protein domains that interact with these conserved motifs. We predicted which human proteins may be targeted by HIV-1 by taking pairs of human proteins that may interact via a motif conserved in HIV-1 and the corresponding interacting protein domain., Results: Our predictions were enriched with host proteins known to interact with HIV-1 proteins ENV, NEF, and TAT (p-value < 4.26E-21). Cellular pathways statistically enriched for our predictions include the T cell receptor signaling, natural killer cell mediated cytotoxicity, cell cycle, and apoptosis pathways. Gene Ontology molecular function level 5 categories enriched with both predicted and confirmed HIV-1 targeted proteins included categories associated with phosphorylation events and adenyl ribonucleotide binding., Conclusion: A list of host proteins highly enriched with those targeted by HIV-1 proteins can be obtained by searching for host protein motifs along virus protein sequences. The resulting set of host proteins predicted to be targeted by virus proteins will become more accurate with better annotations of motifs and domains. Nevertheless, our study validates the role of linear binding motifs shared by virus and host proteins as an important part of the crosstalk between virus and host.

Background: Gene expression is controlled over a wide range at the transcript level through complex interplay between DNA and regulatory proteins, resulting in profiles of gene expression that can be represented as normal, graded, and bimodal (switch-like) distributions. We have previously performed genome-scale identification and annotation of genes with switch-like expression at the transcript level in mouse, using large microarray datasets for healthy tissue, in order to study the cellular pathways and regulatory mechanisms involving this class of genes. We showed that a large population of bimodal mouse genes encoding for cell membrane and extracellular matrix proteins is involved in communication pathways. This study expands on previous results by annotating human bimodal genes, investigating their correspondence to bimodality in mouse orthologs and exploring possible regulatory mechanisms that contribute to bimodality in gene expression in human and mouse., Results: Fourteen percent of the human genes on the HGU133A array (1847 out of 13076) were identified as bimodal or switch-like. More than 40% were found to have bimodal mouse orthologs. KEGG pathways enriched for bimodal genes included ECM-receptor interaction, focal adhesion, and tight junction, showing strong similarity to the results obtained in mouse. Tissue-specific modes of expression of bimodal genes among brain, heart, and skeletal muscle were common between human and mouse. Promoter analysis revealed a higher than average number of transcription start sites per gene within the set of bimodal genes. Moreover, the bimodal gene set had differentially methylated histones compared to the set of the remaining genes in the genome., Conclusion: The fact that bimodal genes were enriched within the cell membrane and extracellular environment make these genes as candidates for biomarkers for tissue specificity. The commonality of the important roles bimodal genes play in tissue differentiation in both the human and mouse indicates the potential value of mouse data in providing context for human tissue studies. The regulation motifs enriched in the bimodal gene set (TATA boxes, alternative promoters, methlyation) have known associations with complex diseases, such as cancer, providing further potential for the use of bimodal genes in studying the molecular basis of disease.

Background: Large-scale compilation of gene expression microarray datasets across diverse biological phenotypes provided a means of gathering a priori knowledge in the form of identification and annotation of bimodal genes in the human and mouse genomes. These switch-like genes consist of 15% of known human genes, and are enriched with genes coding for extracellular and membrane proteins. It is of interest to determine the prediction potential of bimodal genes for class discovery in large-scale datasets., Results: Use of a model-based clustering algorithm accurately classified more than 400 microarray samples into 19 different tissue types on the basis of bimodal gene expression. Bimodal expression patterns were also highly effective in differentiating between infectious diseases in model-based clustering of microarray data. Supervised classification with feature selection restricted to switch-like genes also recognized tissue specific and infectious disease specific signatures in independent test datasets reserved for validation. Determination of "on" and "off" states of switch-like genes in various tissues and diseases allowed for the identification of activated/deactivated pathways. Activated switch-like genes in neural, skeletal muscle and cardiac muscle tissue tend to have tissue-specific roles. A majority of activated genes in infectious disease are involved in processes related to the immune response., Conclusion: Switch-like bimodal gene sets capture genome-wide signatures from microarray data in health and infectious disease. A subset of bimodal genes coding for extracellular and membrane proteins are associated with tissue specificity, indicating a potential role for them as biomarkers provided that expression is altered in the onset of disease. Furthermore, we provide evidence that bimodal genes are involved in temporally and spatially active mechanisms including tissue-specific functions and response of the immune system to invading pathogens.

Background: Recent studies have placed gene expression in the context of distribution profiles including housekeeping, graded, and bimodal (switch-like). Single-gene studies have shown bimodal expression results from healthy cell signaling and complex diseases such as cancer, however developing a comprehensive list of human bimodal genes has remained a major challenge due to inherent noise in human microarray data. This study presents a two-component mixture analysis of mouse gene expression data for genes on the Affymetrix MG-U74Av2 array for the detection and annotation of switch-like genes. Two-component normal mixtures were fit to the data to identify bimodal genes and their potential roles in cell signaling and disease progression., Results: Seventeen percent of the genes on the MG-U74Av2 array (1519 out of 9091) were identified as bimodal or switch-like. KEGG pathways significantly enriched for bimodal genes included ECM-receptor interaction, cell communication, and focal adhesion. Similarly, the GO biological process "cell adhesion" and cellular component "extracellular matrix" were significantly enriched. Switch-like genes were found to be associated with such diseases as congestive heart failure, Alzheimer's disease, arteriosclerosis, breast neoplasms, hypertension, myocardial infarction, obesity, rheumatoid arthritis, and type I and type II diabetes. In diabetes alone, over two hundred bimodal genes were in a different mode of expression compared to normal tissue., Conclusion: This research identified and annotated bimodal or switch-like genes in the mouse genome using a large collection of microarray data. Genes with bimodal expression were enriched within the cell membrane and extracellular environment. Hundreds of bimodal genes demonstrated alternate modes of expression in diabetic muscle, pancreas, liver, heart, and adipose tissue. Bimodal genes comprise a candidate set of biomarkers for a large number of disease states because their expressions are tightly regulated at the transcription level.

Background: Independently derived expression profiles of the same biological condition often have few genes in common. In this study, we created populations of expression profiles from publicly available microarray datasets of cancer (breast, lymphoma and renal) samples linked to clinical information with an iterative machine learning algorithm. ROC curves were used to assess the prediction error of each profile for classification. We compared the prediction error of profiles correlated with molecular phenotype against profiles correlated with relapse-free status. Prediction error of profiles identified with supervised univariate feature selection algorithms were compared to profiles selected randomly from a) all genes on the microarray platform and b) a list of known disease-related genes (a priori selection). We also determined the relevance of expression profiles on test arrays from independent datasets, measured on either the same or different microarray platforms., Results: Highly discriminative expression profiles were produced on both simulated gene expression data and expression data from breast cancer and lymphoma datasets on the basis of ER and BCL-6 expression, respectively. Use of relapse-free status to identify profiles for prognosis prediction resulted in poorly discriminative decision rules. Supervised feature selection resulted in more accurate classifications than random or a priori selection, however, the difference in prediction error decreased as the number of features increased. These results held when decision rules were applied across-datasets to samples profiled on the same microarray platform., Conclusion: Our results show that many gene sets predict molecular phenotypes accurately. Given this, expression profiles identified using different training datasets should be expected to show little agreement. In addition, we demonstrate the difficulty in predicting relapse directly from microarray data using supervised machine learning approaches. These findings are relevant to the use of molecular profiling for the identification of candidate biomarker panels.

Helicobacter pylori (H. pylori), a gram-negative bacterium, infects the stomach of approximately 50% of the world population. H. pylori infection is a risk factor for developing chronic gastric ulcers and gastric cancer. The bacteria produce two main cytotoxic proteins: Vacuolating cytotoxin A (VacA) and Cytotoxin-Associated gene A (CagA). When these proteins enter the host cell they interfere with the host MAP Kinase and Apoptosis signaling pathways leading to aberrant cell growth and premature apoptosis. The present study expanded existing quantitative models of the MAP Kinase and Apoptosis signaling pathways to take into account the protein interactions across species using the CellDesigner tool. The resulting network contained hundreds of differential equations in which the coefficients for the biochemical rate constants were estimated from previously published studies. The effect of VacA and CagA on the function of this network were simulated by increasing levels of bacterial load. Simulations showed that increasing bacterial load affected the MAP Kinase signaling in a dose dependant manner. The introduction of CagA decreased the activation time of mapK signaling and extended activation indefinitely despite normal cellular activity to deactivate the protein. Introduction of VacA produced a similar response in the apoptosis pathway. Bacterial load activated both pathways even in the absence of external stimulation. Time course of emergence of transcription factors associated with cell division and cell death predicted by our simulation showed close agreement with that determined from a publicly accessible microarray data set of H. pylori infected stomach epithelium. The quantitative model presented in this study lays the foundation for investigating the affects of single nucleotide polymorphisms (SNPs) on the efficiency of drug treatment.

At various stages during embryogenesis and cancer cells are exposed to tension, compression and shear stress; forces that can regulate cell proliferation and differentiation. In the present study, we show that shear stress blocks cell cycle progression in colon cancer cells and regulates the expression of genes linked to the Wnt/beta-catenin, mitogen-activated protein kinase (MAPK) and NFkappaB pathways. The shear stress-induced increase of the secreted Wnt inhibitor DKK1 requires p38 and activation of NFkappaB requires IkappaB kinase-beta. Activation of beta-catenin, important in Wnt signaling and the cause of most colon cancers, is inhibited by shear stress through a pathway involving laminin-5, alpha6beta4 integrin, phosphoinositide 3-kinase (PI 3-kinase) and Rac1 coupled with changes in the distribution of dephosphorylated beta-catenin. These data show that colon cancer cells respond to fluid shear stress by activation of specific signal transduction pathways and genetic regulatory circuits to affect cell proliferation, and indicate that the response of colon cancers to mechanical forces such as fluid shear stress should be taken into account in the management of the disease.

Breast tumors are typically heterogeneous and contain diverse subpopulations of tumor cells with differing phenotypic properties. Planar cultures of cancer cell lines are not viable models of investigation of cell-cell and cell-matrix interactions during tumor development. This article presents an in vitro coculture-based 3-dimensional heterogeneous breast tumor model that can be used in drug resistance and drug delivery investigations. Breast cancer cell lines of different phenotypes (MDAMB231, MCF7, and ZR751) were cocultured in a rotating wall vessel bioreactor to form a large number of heterogeneous tumoroids in a single cell culture experiment. Cells in the rotating vessels were labeled with Cell Tracker fluorescent probes to allow for time course fluorescence microscopy to monitor cell aggregation. Histological sections of tumoroids were stained with hematoxylin and eosin, progesterone receptor, E-cadherin (E-cad), and proliferation marker ki67. In vitro tumoroids developed in this study recapture important features of the temporal-spatial organization of solid tumors, including the presence of necrotic areas at the center and higher levels of cell division at the tumor periphery. E-cad-positive MCF7 cells form larger tumoroids than E-cad-negative MDAMB231 cells. In heterogeneous tumors, the irregular surface roughness was mainly due to the presence of MDAMB231 cells, whereas MCF7 cells formed smooth surfaces. Moreover, when heterogeneous tumoroids were placed onto collagen gels, highly invasive MDAMB231 cell-rich surface regions produced extensions into the matrix, whereas poorly invasive MCF7 cells did not. The fact that one can form a large number of 1-mm tumoroids in 1 coculture attests to the potential use of this system at high-throughput investigations of cancer drug development and drug delivery into the tumor.

Background: Cell lines are used in experimental investigation of cancer but their capacity to represent tumor cells has yet to be quantified. The aim of the study was to identify significant alterations in pathway usage in cell lines in comparison with normal and tumor tissue., Methods: This study utilized a pathway-specific enrichment analysis of publicly accessible microarray data and quantified the gene expression differences between cell lines, tumor, and normal tissue cells for six different tissue types. KEGG pathways that are significantly different between cell lines and tumors, cell lines and normal tissues and tumor and normal tissue were identified through enrichment tests on gene lists obtained using Significance Analysis of Microarrays (SAM)., Results: Cellular pathways that were significantly upregulated in cell lines compared to tumor cells and normal cells of the same tissue type included ATP synthesis, cell communication, cell cycle, oxidative phosphorylation, purine, pyrimidine and pyruvate metabolism, and proteasome. Results on metabolic pathways suggested an increase in the velocity nucleotide metabolism and RNA production. Pathways that were downregulated in cell lines compared to tumor and normal tissue included cell communication, cell adhesion molecules (CAMs), and ECM-receptor interaction. Only a fraction of the significantly altered genes in tumor-to-normal comparison had similar expressions in cancer cell lines and tumor cells. These genes were tissue-specific and were distributed sparsely among multiple pathways., Conclusion: Significantly altered genes in tumors compared to normal tissue were largely tissue specific. Among these genes downregulation was a major trend. In contrast, cell lines contained large sets of significantly upregulated genes that were common to multiple tissue types. Pathway upregulation in cell lines was most pronounced over metabolic pathways including cell nucleotide metabolism and oxidative phosphorylation. Signaling pathways involved in adhesion and communication of cultured cancer cells were downregulated. The three way pathways comparison presented in this study brings light into the differences in the use of cellular pathways by tumor cells and cancer cell lines.

Background: Tumor classification is inexact and largely dependent on the qualitative pathological examination of the images of the tumor tissue slides. In this study, our aim was to develop an automated computational method to classify Hematoxylin and Eosin (H&E) stained tissue sections based on cancer tissue texture features., Methods: Image processing of histology slide images was used to detect and identify adipose tissue, extracellular matrix, morphologically distinct cell nuclei types, and the tubular architecture. The texture parameters derived from image analysis were then applied to classify images in a supervised classification scheme using histologic grade of a testing set as guidance., Results: The histologic grade assigned by pathologists to invasive breast carcinoma images strongly correlated with both the presence and extent of cell nuclei with dispersed chromatin and the architecture, specifically the extent of presence of tubular cross sections. The two parameters that differentiated tumor grade found in this study were (1) the number density of cell nuclei with dispersed chromatin and (2) the number density of tubular cross sections identified through image processing as white blobs that were surrounded by a continuous string of cell nuclei. Classification based on subdivisions of a whole slide image containing a high concentration of cancer cell nuclei consistently agreed with the grade classification of the entire slide., Conclusion: The automated image analysis and classification presented in this study demonstrate the feasibility of developing clinically relevant classification of histology images based on micro- texture. This method provides pathologists an invaluable quantitative tool for evaluation of the components of the Nottingham system for breast tumor grading and avoid intra-observer variability thus increasing the consistency of the decision-making process.

Recent mathematical models show that molecular events that mediate rolling interactions also have an impact on the stochastic features of rolling. In spherical cells, statistical fluctuations in cell displacement were shown to be an indication that only a few adhesion bonds are involved in rolling interactions. In this study, we investigated whether cell shape and cell deformability could also modulate the stochastic features of rolling. As an experimental model we considered the flow-initiated rolling of MCF-10 breast epithelial cells on laminin. The dynamic adhesion of MCF-10A cells to laminin, which involves integrin alpha 6 beta 4, occurs slow enough to allow for an accurate determination of the trajectories of rolling cells. The data from high-magnification videomicroscopy showed that cell shape, cell deformability, and the level of fluid shear stress were all strong determinants of the rolling velocity and the extent of fluctuations in the trajectory of rolling cells. MCF-10A cells with large surface projections rolled faster and wobbled more extensively than spherical cells under the same flow conditions. The extent of wobbling decreased and the variation of rolling velocity increased with increasing fluid shear stress. MCF-10A cells treated with cytochalasin B, which increased cell deformability and caused extensive blebbing without significantly altering surface expression of laminin integrins, reduced mean rolling velocity and increased its variance. Because leukocytes change shape as they roll in postcapillary blood venules at high shear rates, results indicate the need for further expanding the present biophysical models of rolling to the case of deformable cells.

Vinculin, a 117-kDa protein, is a constituent of adhesion plaques and adherence junctions in non-muscle cells. We investigated the role of vinculin on the physical strength of cell-cell adhesion by conducting disaggregation assays on aggregates of parental wild-type F9 mouse embryonal carcinoma cells (clone BIM), two vinculin-depleted F9 cell lines, gamma 227 and gamma 229, and a reconstituted gamma 229 cell line (R3) that re-express vinculin. Immunoblotting demonstrated that the four cell lines used in the study had similar expressions of the cell-cell adhesion molecule E-cadherin and associated membrane proteins alpha- and beta-catenin. Double immunofluorescence analysis showed that, in contrast to the vinculin-null cell lines. BIM and R3 cells expressed abundant vinculin at the cell margins in adhesion plaques and in cell-cell margins that also contained actin. Laminar flow assays showed that both the vinculin-positive and vinculin-negative cell aggregates that were formed in culture in the course of 24 to 48 hours largely remained intact despite the imposition of shear flow at high shear rates. Since laminar flow imposed on cell aggregates act to separate cells from each other, our data indicate that F9 cells that were adherent to a substrate formed strong cell-cell adhesion bonds independent of vinculin expression. On the other hand, aggregates of vinculin-depleted gamma 229 and gamma 227 cells that were formed in suspension during a two-hour static incubation at 37 degrees C were desegregated more easily with the imposition of shear flow than the BIM and R3 cell aggregates formed under identical conditions. Loss of vinculin was associated with a reduction in cell-cell adhesion strength only among those cells lacking contact to a substrate. Overall, the results indicate that vinculin is not needed for forming strong cell-cell adhesion bonds between neighboring carcinoma cells which are adherent to the basal lamina.

In this study we show that a breast cancer cell line (SKBR3) that expresses no E-cadherin and very low levels of beta-catenin protein and exhibits a poorly adhesive phenotype in Matrigel responds to retinoic acid (RA) by a marked increase in epithelial differentiation. Specifically, treatment of cells with all-trans-RA, 9-cis-RA, or a RA receptor alpha-specific ligand resulted in a large increase in cell-cell adhesive strength and stimulated the formation of fused cell aggregates in Matrigel. A retinoid X receptor-specific ligand was ineffective. Exposure of cells to 9-cis-RA for as little as 4 h was sufficient to maintain the adhesive phenotype for at least 4 days. The effects of 9-cis-RA required protein and RNA synthesis, but were not mediated by factors secreted by stimulated cells or by direct cell contact and did not require serum. These 9-cis-RA-induced morphological effects were completely reversed by growing cells in 50 microM Ca2+, suggesting a mechanism involving a 9-cis-RA-induced increase in Ca(2+)-dependent adhesion. Consistent with this, beta-catenin protein levels were markedly elevated in the 9-cis-RA-treated cells, and beta-catenin became localized to a Triton-insoluble pool at regions of cell-cell contact. No change could be detected in beta-catenin steady state messenger RNA levels, but 9-cis-RA did increase beta-catenin protein stability. Treatment of cells with low calcium medium did not prevent the 9-cis-RA-induced increase in total beta-catenin protein, but did prevent its movement to a Triton-insoluble pool at the cell membrane. Among several kinase inhibitors, only the broad spectrum kinase inhibitor staurosporine and the protein kinase C inhibitor bisindoylmaleimide reversed the morphological changes induced by 9-cis-RA. Like treatment with low calcium medium, these inhibitors did not prevent the 9-cis-RA-induced increase in total beta-catenin protein levels, but completely prevented the movement of beta-catenin to the cell membrane. These results point to a role for beta-catenin and serine kinase activity in mediating the action of 9-cis-RA in epithelial differentiation.

Defects in the expression or function of the calcium dependent cell-cell adhesion molecule E-cadherin are common in invasive, metastatic carcinomas. In the present study the response of aggregates of breast epithelial cells and breast and colon carcinoma cells to forces imposed by laminar flow in a parallel plate flow channel was examined. Although E-cadherin negative tumor cells formed cell aggregates in the presence of calcium, these were significantly more likely than E-cadherin positive cell aggregates to disaggregate in response to low shear forces, such as those found in a lymphatic vessel or venule (< 3.5 dyn/cm2). E-cadherin positive normal breast epithelial cells and E-cadherin positive breast tumor cell aggregates could not be disaggregated when exposed to shear forces in excess of those found in arteries (> 100 dyn/cm2). E-cadherin negative cancer cells which had been transfected with E-cadherin exhibited large increases in adhesion strength only if the expressed protein was appropriately linked to the cytoskeleton. These results show that E-cadherin negative tumor cells, or cells in which the adhesion molecule is present but is inefficiently linked to the cytoskeleton, are far more likely than E-cadherin positive cells to detach from a tumor mass in response to low shear forces, such as those found in a lymphatic vessel or venule. Since a primary route of dissemination of many carcinoma cells is to the local lymph nodes these results point to a novel mechanism whereby defects in cell-cell adhesion could lead to carcinoma cell dissemination.

In the present study we investigate the transient conjugation of cell pairs by using a mathematical model. Macromolecules responsible for adhesion (bonds) are assumed to exist in two reversible states, attached and unattached, and exert a force elastic in nature only when they cross-link the two cell surfaces (attached state). Bonds form a link between the two cell surfaces only in the attached form. The unattached bridges are assumed laterally mobile in the plane of the cell membrane. Lateral mobility of attached bonds may be limited by structures on the undersurface of the cell membrane. Using this model we show that the bond density distribution between a cytotoxic T-cell (F-1) and a cancer cell (JY:HLA-A2-B7-DR4, W6) approaches equilibrium within 10 min, the incubation period used in experiments by Sung, K.L.P., L.A. Sung, M. Crimmins, S.J. Burakoff, and S. Chien (1986. Science [Wash. DC]. 234:1405-1408). If the diffusion coefficient of attached bonds is set equal to zero in the computations the model predictions indicate accumulation of bonds at the edge of conjugation. This prediction is consistent with present experimental data on lectin-induced red blood cell aggregation (Vayo, M., R. Skalak, P. Brunn, S. Usami, and S. Chien. 1987. Fed. Proc. 46:1043). It is concluded that significant features of micromanipulation data on specific adhesion can be explained by the diffusivity properties of bonds responsible for adhesion.

Cell-cell adhesion plays a fundamental role in tissue and organ development, cell mediated immunity and blood flow. In the present study a micro-mechanical model of specific adhesion is presented. Analytical expressions are derived for the adhesive energy density (gamma) at zero speed of peeling for the cases of immobile (trapped) as well as laterally mobile bonds. It is shown that gamma increases in both cases with the increasing density of bonds and with the binding of affinity of unstressed bonds. In the case of laterally mobile bonds gamma also increases with the extent of peeling. The analytical results are shown to be valid whether or not one takes into account of the bending stiffness of adhering membranes. It is also shown that gamma does not depend on the functional form of bond elasticity. The effect of the speed of peeling on the number density distribution of attached bonds is considered next. Numerical solutions for the energy required to separate conjugated cell pairs are presented. The theoretical predictions are then used to analyze experimental data on red cell aggregation and adhesion between a cytotoxic-T cell and its target cell. The results show that the binding affinity of unstressed bonds and their number density before conjugation can be obtained from data on slow peeling of cell-pairs. The information on the diffusivity of bonds, their stiffness and their rates of attachment and detachment are more difficult to obtain, requiring a set of experiments with increasing rates of separation (conjugation) of cell-pairs.

Recent experiments on cell-cell adhesion indicate that (i) bonds between two cells migrate towards the region of conjugation during peeling, and (ii) cell membrane tension increases with the rate of peeling. Analytical methods that would allow the derivation of intrinsic parameters of adhesion from such experimental data have yet to be explored. In this study we introduce a specific adhesion model to investigate the complex interaction between rate of peeling, lateral diffusivity and the rate of detachment of bonds. Our analysis show that adhesive energy density increases with the rate of peeling and with lateral diffusivity of the bonds but decreases with increasing rate of detachment. The rate dependency of the adhesive energy is due to the modulation of the number density distribution of bonds by the speed of peeling.

A simple model of a double-headed crossbridge is introduced to explain the retardation of force decay after an imposed stretch in skeletal muscle fibers under equilibrium conditions. The critical assumption in the model is that once one of the heads of a crossbridge is attached to one of the available actin sites, the attachment of the second head will be restricted to a level of strain determined by the attachment of the first head. The crossbridge structure, namely the connection of both heads of a crossbridge to the same tail region, is assumed to impose this constraint on the spatial configurations of crossbridge heads. The unique feature of the model is the prediction that, in the presence of a ligand (PPi, ADP, AMP-PNP) and absence of Ca2+, the halftime of force decay is many times larger than the inverse rate of detachment of a crossbridge head measured in solution. This prediction is in agreement with measured values of half-times of force decay in fibers under similar conditions (Schoenberg, M., and E. Eisenberg. 1985. Biophys. J. 48:863-871f). It is predicted that a crossbridge head is more likely to re-attach to its previously strained position than remain unattached while the other head is attached, leading to the slow decay of force. Our computations also show that the apparent cooperativity in crossbridge binding observed in experiments (Brenner, B., L. C. Yu, L. E. Greene, E. Eisenberg, and M. Schoenberg. 1986. Biophys. J. 50:1101-1108) can be partially accounted by the double-headed crossbridge attachment. Our model predictions fit the aforementioned data best when the crossbridge stiffness does not change significantly with the dissociation of one of the two attached heads. This observation suggests that crossbridge stiffness is determined either by the extensibility (flexibility) of the double helical tail region or its junction to the thick filament backbone.

A micromanipulation method is used to determine the adhesive energy density (gamma) between pairs of cytotoxic T cells (F1) and their target cells (JY: HLA-A2-B7-DR4,W6). gamma is defined as the energy per unit area that must be supplied to reduce the region of contact between a conjugated cell pair. Our analysis of the data indicates that the force applied by the micropipette on the cell is not uniformly distributed throughout the contact region as we had previously assumed (Sung, K. L. P., L. A. Sung, M. Crimmins, S. J. Burakoff, and S. Chien. 1986. Science (Wash. DC). 234: 1405-1408), but acts only at the edges of the contact region. We show that gamma is not constant during peeling but increases with decreasing contact area of the conjugated cell pairs F1-JY, F1-F1, and JY-JY in contrast to the constancy of gamma for typical engineering adhesives. This finding supports the notion that the cross-linking protein molecules slide towards the conjugated area across the leading edge of the separation while remaining attached to both cells. Our mathematical analysis shows that the elastic energy stored in the cross-links by the membrane tensions balances the diffusive forces that act against cross-bridge migration. The binding affinity between F1-JY is found to be approximately 15-20 times larger than the corresponding affinity for F1-F1. The number of binding sites of F1 for attachment to JY is approximately the same for binding F1 to another F1 and vary between 10(5) and 10(6).

The several widely different values of the elastic modulus of the human red blood cell membrane which have been reported in the literature are incorporated into a single strain energy function consisting of two terms. One term gives the small stresses and low elastic modulus which is observed when the red cell membrane is deformed at constant area. The second term contributes a large isotropic stress dependent on the change of area. The strain energy function is applied to the process of sphering of red blood cells in a hypotonic solution. It is shown that a nearly perfect sphere can result even though the red blood cell membrane is homogeneous in all areas of the cell. Results pertinent to sieving and micropipette experiments are also explored.