Angel E. Dago

Structural basis of histidine kinase autophosphorylation deduced by integrating genomics, molecular dynamics, and mutagenesis

Signal transduction proteins such as bacterial sensor histidine kinases, designed to transition between multiple conformations, are often ruled by unstable transient interactions making structural characterization of all functional states difficult. This study explored the inactive and signal-activated conformational states of the two catalytic domains of sensor histidine kinases, HisKA and HATPase. Direct coupling analyses, a global statistical inference approach, was applied to >13,000 such domains from protein databases to identify residue contacts between the two domains. These contacts guided structural assembly of the domains using MAGMA, an advanced molecular dynamics docking method. The active conformation structure generated by MAGMA simultaneously accommodated the sequence derived residue contacts and the ATP-catalytic histidine contact. The validity of this structure was confirmed biologically by mutation of contact positions in the Bacillus subtilis sensor histidine kinase KinA and by restoration of activity in an inactive KinA(HisKA):KinD(HATPase) hybrid protein. These data indicate that signals binding to sensor domains activate sensor histidine kinases by causing localized strain and unwinding at the end of the C-terminal helix of the HisKA domain. This destabilizes the contact positions of the inactive conformation of the two domains, identified by previous crystal structure analyses and by the sequence analysis described here, inducing the formation of the active conformation. This study reveals that structures of unstable transient complexes of interacting proteins and of protein domains are accessible by applying this combination of cross-validating technologies.

Multiple orphan histidine kinases interact directly with Spo0A to control the initiation of endospore formation in Clostridium acetobutylicum

The phosphorylated Spo0A transcription factor controls the initiation of endospore formation in Clostridium acetobutylicum, but genes encoding key phosphorelay components, Spo0F and Spo0B, are missing in the genome. We hypothesized that the five orphan histidine kinases of C. acetobutylicum interact directly with Spo0A to control its phosphorylation state. Sequential targeted gene disruption and gene expression profiling provided evidence for two pathways for Spo0A activation, one dependent on a histidine kinase encoded by cac0323, the other on both histidine kinases encoded by cac0903 and cac3319. Purified Cac0903 and Cac3319 kinases autophosphorylated and transferred phosphoryl groups to Spo0A in vitro, confirming their role in Spo0A activation in vivo. A cac0437 mutant hyper‐sporulated, suggesting that Cac0437 is a modulator that prevents sporulation and maintains cellular Spo0A∼P homeostasis during growth. Accordingly, Cac0437 has apparently lost the ability to autophosphorylate in vitro; instead it catalyses the ATP‐dependent dephosphorylation of Spo0A∼P releasing inorganic phosphate. Direct phosphorylation of Spo0A by histidine kinases and dephosphorylation by kinase‐like proteins may be a common feature of the clostridia that may represent the ancestral state before the great oxygen event some 2.4 billion years ago, after which additional phosphorelay proteins were recruited in the evolutionary lineage that led to the bacilli.

Rapid Phenotypic and Genomic Change in Response to Therapeutic Pressure in Prostate Cancer Inferred by High Content Analysis of Single Circulating Tumor Cells

Timely characterization of a cancers evolution is required to predict treatment efficacy and to detect resistance early. High content analysis of single Circulating Tumor Cells (CTCs) enables sequential characterization of genotypic, morphometric and protein expression alterations in real time over the course of cancer treatment. This concept was investigated in a patient with castrate-resistant prostate cancer progressing through both chemotherapy and targeted therapy. In this case study, we integrate across four timepoints 41 genome-wide copy number variation (CNV) profiles plus morphometric parameters and androgen receptor (AR) protein levels. Remarkably, little change was observed in response to standard chemotherapy, evidenced by the fact that a unique clone (A), exhibiting highly rearranged CNV profiles and AR+ phenotype was found circulating before and after treatment. However, clinical response and subsequent progression after targeted therapy was associated with the drastic depletion of clone A, followed by the sequential emergence of two distinct CTC sub-populations that differed in both AR genotype and expression phenotype. While AR- cells with flat or pseudo-diploid CNV profiles (clone B) were identified at the time of response, a new tumor lineage of AR+ cells (clone C) with CNV altered profiles was detected during relapse. We showed that clone C, despite phylogenetically related to clone A, possessed a unique set of somatic CNV alterations, including MYC amplification, an event linked to hormone escape. Interesting, we showed that both clones acquired AR gene amplification by deploying different evolutionary paths. Overall, these data demonstrate the timeframe of tumor evolution in response to therapy and provide a framework for the multi-scale analysis of fluid biopsies to quantify and monitor disease evolution in individual patients.

Chromosomal Instability Estimation Based on Next Generation Sequencing and Single Cell Genome Wide Copy Number Variation Analysis

Genomic instability is a hallmark of cancer often associated with poor patient outcome and resistance to targeted therapy. Assessment of genomic instability in bulk tumor or biopsy can be complicated due to sample availability, surrounding tissue contamination, or tumor heterogeneity. The Epic Sciences circulating tumor cell (CTC) platform utilizes a non-enrichment based approach for the detection and characterization of rare tumor cells in clinical blood samples. Genomic profiling of individual CTCs could provide a portrait of cancer heterogeneity, identify clonal and sub-clonal drivers, and monitor disease progression. To that end, we developed a single cell Copy Number Variation (CNV) Assay to evaluate genomic instability and CNVs in patient CTCs. For proof of concept, prostate cancer cell lines, LNCaP, PC3 and VCaP, were spiked into healthy donor blood to create mock patient-like samples for downstream single cell genomic analysis. In addition, samples from seven metastatic castration resistant prostate cancer (mCRPC) patients were included to evaluate clinical feasibility. CTCs were enumerated and characterized using the Epic Sciences CTC Platform. Identified single CTCs were recovered, whole genome amplified, and sequenced using an Illumina NextSeq 500. CTCs were then analyzed for genome-wide copy number variations, followed by genomic instability analyses. Large-scale state transitions (LSTs) were measured as surrogates of genomic instability. Genomic instability scores were determined reproducibly for LNCaP, PC3, and VCaP, and were higher than white blood cell (WBC) controls from healthy donors. A wide range of LST scores were observed within and among the seven mCRPC patient samples. On the gene level, loss of the PTEN tumor suppressor was observed in PC3 and 5/7 (71%) patients. Amplification of the androgen receptor (AR) gene was observed in VCaP cells and 5/7 (71%) mCRPC patients. Using an in silico down-sampling approach, we determined that DNA copy number and genomic instability can be detected with as few as 350K sequencing reads. The data shown here demonstrate the feasibility of detecting genomic instabilities at the single cell level using the Epic Sciences CTC Platform. Understanding CTC heterogeneity has great potential for patient stratification prior to treatment with targeted therapies and for monitoring disease evolution during treatment.

Abstract 4599: Sequential monitoring of single-cell copy number variation in metastatic prostate cancer.

Proceedings: AACR 104th Annual Meeting 2013; Apr 6-10, 2013; Washington, DC The high-definition circulating tumor cell (HD-CTC) assay provides for an enrichment-free approach to CTC identification. Here, we utilized the HD-CTC approach to study androgen receptor (AR) expression combined with single-nucleus sequencing for genome-wide analysis of copy number variation (CNV) in sequential CTCs samples obtained from a patient with metastatic prostate cancer treated with abiraterone acetate (an androgen synthesis inhibitor). At baseline, before initiation of abiraterone treatment, we observed a balanced proportion of AR-negative and AR-positive CTCs. During a brief period of clinical response (marked with a decreased serum PSA and decreased pain) the proportion of AR-positive CTCs declined followed by a rapid increase associated with clinical progression (increased PSA and pain). CNV analysis of single CTCs revealed multiple genomic rearrangements, such as AR amplification along with the chromosomal gains and losses typical of prostate cancer, in multiple cells at baseline. During treatment response, the frequency of CNV alterations significantly declined, followed by a reemergence to a pattern of multiple, complex alterations associated with clinical progression. Detailed analysis of the CNV profiles revealed that many abnormalities were commonly shared between the CTC populations, but a number were unique to the AR+ resistant/hormone refractory CTC population including increased MYC amplification alteration and the AR amplicon that include additional adjacent genes. Remarkably, the reconstruction of tumor lineage history based on the CTC genomic profiles enables us to trace and identify the precise treatment time point where the putative therapy-resistant CTC clone emerges, under therapeutic pressure, until it eventually expanded to become the AR+ resistant CTC population at the point of therapeutic relapse. Overall, our results demonstrated that the integration of the HD-CTC enumeration technology with protein expression and single cell genomic analyses could successfully be applied to real time monitoring of ADT therapy emergent change in a prostate cancer patient, and may provide a direct roadmap for personalized cancer medicine in the near future. Citation Format: Peter Kuhn, Angel E. Dago, Asya Stepansky, Anders Carlsson, Natalie Felch, Madelyn Luttgen, Anand Kolatkar, James Hicks, Mitchell E. Gross. Sequential monitoring of single-cell copy number variation in metastatic prostate cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4599. doi:10.1158/1538-7445.AM2013-4599