A graphical model approach to automated classification of protein subcellular location patterns in multi-cell images

BACKGROUND: Knowledge of the subcellular location of a protein is critical to understanding how that protein works in a cell. This location is frequently determined by the interpretation of fluorescence microscope images. In recent years, automated systems have been developed for consistent and objective interpretation of such images so that the protein pattern in a single cell can be assigned to a known location category. While these systems perform with nearly perfect accuracy for single cell images of all major subcellular structures, their ability to distinguish subpatterns of an organelle (such as two Golgi proteins) is not perfect. Our goal in the work described here was to improve the ability of an automated system to decide which of two similar patterns is present in a field of cells by considering more than one cell at a time. Since cells displaying the same location pattern are often clustered together, considering multiple cells may be expected to improve discrimination between similar patterns. RESULTS: We describe how to take advantage of information on experimental conditions to construct a graphical representation for multiple cells in a field. Assuming that a field is composed of a small number of classes, the classification accuracy can be improved by allowing the computed probability of each pattern for each cell to be influenced by the probabilities of its neighboring cells in the model. We describe a novel way to allow this influence to occur, in which we adjust the prior probabilities of each class to reflect the patterns that are present. When this graphical model approach is used on synthetic multi-cell images in which the true class of each cell is known, we observe that the ability to distinguish similar classes is improved without suffering any degradation in ability to distinguish dissimilar classes. The computational complexity of the method is sufficiently low that improved assignments of classes can be obtained for fields of twelve cells in under 0.04 second on a 1600 megahertz processor. CONCLUSION: We demonstrate that graphical models can be used to improve the accuracy of classification of subcellular patterns in multi-cell fluorescence microscope images. We also describe a novel algorithm for inferring classes from a graphical model. The performance and speed suggest that the method will be particularly valuable for analysis of images from high-throughput microscopy. We also anticipate that it will be useful for analyzing the mixtures of cell types typically present in images of tissues. Lastly, we anticipate that the method can be generalized to other problems

Dominant Role of Oncogene Dosage and Absence of Tumor Suppressor Activity in Nras-Driven Hematopoietic Transformation

Biochemical properties of Ras oncoproteins and their transforming ability strongly support a dominant mechanism of action in tumorigenesis. However, genetic studies unexpectedly suggested that wild-type (WT) Ras exerts tumor suppressor activity. Expressing oncogenic Nras[superscript G12D] in the hematopoietic compartment of mice induces an aggressive myeloproliferative neoplasm that is exacerbated in homozygous mutant animals. Here, we show that increased Nras[superscript G12D] gene dosage, but not inactivation of WT Nras, underlies the aggressive in vivo behavior of Nras[superscript G12D over G12D] hematopoietic cells. Modulating Nras[superscript G12D] dosage had discrete effects on myeloid progenitor growth, signal transduction, and sensitivity to MAP-ERK kinase (MEK) inhibition. Furthermore, enforced WT N-Ras expression neither suppressed the growth of Nras-mutant cells nor inhibited myeloid transformation by exogenous Nras[superscript G12D]. Importantly, NRAS expression increased in human cancer cell lines with NRAS mutations. These data have therapeutic implications and support reconsidering the proposed tumor suppressor activity of WT Ras in other cancers.Pfizer Inc. (PD0325901)National Institutes of Health (U.S.) (Grant R37CA72614)National Institutes of Health (U.S.) (Grant P01CA40046)National Institutes of Health (U.S.) (Grant K08CA134649)Leukemia & Lymphoma Society of America (Specialized Center of Research Award LLS 7019-04))American Lebanese Syrian Associated Charitie

oGNM: online computation of structural dynamics using the Gaussian Network Model

An assessment of the equilibrium dynamics of biomolecular systems, and in particular their most cooperative fluctuations accessible under native state conditions, is a first step towards understanding molecular mechanisms relevant to biological function. We present a web-based system, oGNM that enables users to calculate online the shape and dispersion of normal modes of motion for proteins, oligonucleotides and their complexes, or associated biological units, using the Gaussian Network Model (GNM). Computations with the new engine are 5–6 orders of magnitude faster than those using conventional normal mode analyses. Two cases studies illustrate the utility of oGNM. The first shows that the thermal fluctuations predicted for 1250 non-homologous proteins correlate well with X-ray crystallographic data over a broad range [7.3–15 Å] of inter-residue interaction cutoff distances and the correlations improve with increasing observation temperatures. The second study, focused on 64 oligonucleotides and oligonucleotide–protein complexes, shows that good agreement with experiments is achieved by representing each nucleotide by three GNM nodes (as opposed to one-node-per-residue in proteins) along with uniform interaction ranges for all components of the complexes. These results open the way to a rapid assessment of the dynamics of DNA/RNA-containing complexes. The server can be accessed at

Interleukin-7 receptor mutants initiate early T cell precursor leukemia in murine thymocyte progenitors with multipotent potential

Early T cell precursor acute lymphoblastic leukemia (ETP-ALL) exhibits lymphoid, myeloid, and stem cell features and is associated with a poor prognosis. Whole genome sequencing of human ETP-ALL cases has identified recurrent mutations in signaling, histone modification, and hematopoietic development genes but it remains to be determined which of these abnormalities are sufficient to initiate leukemia. We show that activating mutations in the interleukin-7 receptor identified in human pediatric ETP-ALL cases are sufficient to generate ETP-ALL in mice transplanted with primitive transduced thymocytes from p19(Arf-/-) mice. The cellular mechanism by which these mutant receptors induce ETP-ALL is the block of thymocyte differentiation at the double negative 2 stage at which myeloid lineage and T lymphocyte developmental potential coexist. Analyses of samples from pediatric ETP-ALL cases and our murine ETP-ALL model show uniformly high levels of LMO2 expression, very low to undetectable levels of BCL11B expression, and a relative lack of activating NOTCH1 mutations. We report that pharmacological blockade of Jak-Stat signaling with ruxolitinib has significant antileukemic activity in this ETP-ALL model. This new murine model recapitulates several important cellular and molecular features of ETP-ALL and should be useful to further define novel therapeutic approaches for this aggressive leukemia.Louise M. Treanor, Sheng Zhou, Laura Janke, Michelle L. Churchman, Zhijun Ma, Taihe Lu, Shann-Ching Chen, Charles G. Mullighan, Brian P. Sorrentin

A recurrent germline PAX5 mutation confers susceptibility to pre-B cell acute lymphoblastic leukemia

Somatic alterations of the lymphoid transcription factor gene PAX5 (also known as BSAP) are a hallmark of B cell precursor acute lymphoblastic leukemia (B-ALL)1–3, but inherited mutations of PAX5 have not previously been described. Here we report a new heterozygous germline variant, c.547G>A (p.Gly183Ser), affecting the octapeptide domain of PAX5 that was found to segregate with disease in two unrelated kindreds with autosomal dominant B-ALL. Leukemic cells from all affected individuals in both families exhibited 9p deletion, with loss of heterozygosity and retention of the mutant PAX5 allele at 9p13. Two additional sporadic ALL cases with 9p loss harbored somatic PAX5 substitutions affecting Gly183. Functional and gene expression analysis of the PAX5 mutation demonstrated that it had significantly reduced transcriptional activity. These data extend the role of PAX5 alterations in the pathogenesis of pre-B cell ALL and implicate PAX5 in a new syndrome of susceptibility to pre-B cell neoplasia

Spatial and temporal diversity in genomic instability processes defines lung cancer evolution.

Spatial and temporal dissection of the genomic changes occurring during the evolution of human non-small cell lung cancer (NSCLC) may help elucidate the basis for its dismal prognosis. We sequenced 25 spatially distinct regions from seven operable NSCLCs and found evidence of branched evolution, with driver mutations arising before and after subclonal diversification. There was pronounced intratumor heterogeneity in copy number alterations, translocations, and mutations associated with APOBEC cytidine deaminase activity. Despite maintained carcinogen exposure, tumors from smokers showed a relative decrease in smoking-related mutations over time, accompanied by an increase in APOBEC-associated mutations. In tumors from former smokers, genome-doubling occurred within a smoking-signature context before subclonal diversification, which suggested that a long period of tumor latency had preceded clinical detection. The regionally separated driver mutations, coupled with the relentless and heterogeneous nature of the genome instability processes, are likely to confound treatment success in NSCLC