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.

Treatment response and tumor evolution: lessons from an extended series of multianalyte liquid biopsies in a metastatic breast cancer patient.

Currently, clinical characterization of metastatic breast cancer is based on tissue samples taken at time of diagnosis. However, tissue biopsies are invasive and tumors are continuously evolving, which indicates the need for minimally invasive longitudinal assessment of the tumor. Blood-based liquid biopsies provide minimal invasive means for serial sampling over the course of treatment and the opportunity to adjust therapies based on molecular markers. Here, we aim to identify cellular changes that occur in breast cancer over the lifespan of an affected patient through single-cell proteomic and genomic analysis of longitudinally sampled solid and liquid biopsies. Three solid and 17 liquid biopsies from peripheral blood of an ER+/HER2- metastatic breast cancer patient collected over 4 years and eight treatment regimens were analyzed for morphology, protein expression, copy-number alterations, and single-nucleotide variations. Analysis of 563 single morphometrically similar circulating tumor cells (CTCs) and 13 cell-free DNA (cfDNA) samples along with biopsies of the primary and metastatic tumor revealed progressive genomic evolution away from the primary tumor profiles, along with changes in ER expression and the appearance of resistance mutations. Both the abundance and the genomic alterations of CTCs and cfDNA were highly correlated and consistent with genomic alterations in the tissue samples. We demonstrate that genomic evolution and acquisition of drug resistance can be detected in real time and at single-cell resolution through liquid biopsy analytes and highlight the utility of liquid biopsies to guide treatment decisions.

Morphology-Predicted Large-Scale Transition Number in Circulating Tumor Cells Identifies a Chromosomal Instability Biomarker Associated with Poor Outcome in Castration-Resistant Prostate Cancer.

Chromosomal instability (CIN) increases a tumor cell's ability to acquire chromosomal alterations, a mechanism by which tumor cells evolve, adapt, and resist therapeutics. We sought to develop a biomarker of CIN in circulating tumor cells (CTC) that are more likely to reflect the genetic diversity of patient's disease than a single-site biopsy and be assessed rapidly so as to inform treatment management decisions in real time. Large-scale transitions (LST) are genomic alterations defined as chromosomal breakages that generate chromosomal gains or losses of greater than or equal to10 Mb. Here we studied the relationship between the number of LST in an individual CTC determined by direct sequencing and morphologic features of the cells. This relationship was then used to develop a computer vision algorithm that utilizes CTC image features to predict the presence of a high (9 or more) versus low (8 or fewer) LST number in a single cell. As LSTs are a primary functional component of homologous recombination deficient cellular phenotypes, the image-based algorithm was studied prospectively on 10,240 CTCs in 367 blood samples obtained from 294 patients with progressing metastatic castration-resistant prostate cancer taken prior to starting a standard-of-care approved therapy. The resultant computer vision-based biomarker of CIN in CTCs in a pretreatment sample strongly associated with poor overall survival times in patients treated with androgen receptor signaling inhibitors and taxanes. SIGNIFICANCE: A rapidly assessable biomarker of chromosomal instability in CTC is associated with poor outcomes when detected in men with progressing mCRPC.

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.

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 cancer's 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.

Communication between Esigma(54) , promoter DNA and the conserved threonine residue in the GAFTGA motif of the PspF sigma-dependent activator during transcription activation.

Conversion of Esigma(54) closed promoter complexes to open promoter complexes requires specialized activators which are members of the AAA (ATPases Associated with various cellular Activities) protein family. The ATP binding and hydrolysis activity of Esigma(54) activators is used in an energy coupling reaction to remodel the Esigma(54) closed promoter complex and to overcome the sigma(54)-imposed block on open complex formation. The remodelling target for the AAA activator within the Esigma(54) closed complex includes a complex interface contributed to by Region I of sigma(54), core RNA polymerase and a promoter DNA fork junction structure, comprising the Esigma(54) regulatory centre. One sigma(54) binding surface on Esigma(54) activators is a conserved sequence known as the GAFTGA motif. Here, we present a detailed characterization of the interaction between Region I of sigma(54) and the Escherichia coli AAA sigma(54) activator Phage shock protein F. Using Esigma(54) promoter complexes that mimic different conformations adopted by the DNA during open complex formation, we investigated the contribution of the conserved threonine residue in the GAFTGA motif to transcription activation. Our results suggest that the organization of the Esigma(54) regulatory centre, and in particular the conformation adopted by the sigma(54) Region I and the DNA fork junction structure during open complex formation, is communicated to the AAA activator via the conserved T residue of the GAFTGA motif.