Genomic evolution shapes prostate cancer disease type.

The development of cancer is an evolutionary process involving the sequential acquisition of genetic alterations that disrupt normal biological processes, enabling tumor cells to rapidly proliferate and eventually invade and metastasize to other tissues. We investigated the genomic evolution of prostate cancer through the application of three separate classification methods, each designed to investigate a different aspect of tumor evolution. Integrating the results revealed the existence of two distinct types of prostate cancer that arise from divergent evolutionary trajectories, designated as the Canonical and Alternative evolutionary disease types. We therefore propose the evotype model for prostate cancer evolution wherein Alternative-evotype tumors diverge from those of the Canonical-evotype through the stochastic accumulation of genetic alterations associated with disruptions to androgen receptor DNA binding. Our model unifies many previous molecular observations, providing a powerful new framework to investigate prostate cancer disease progression.

Intra-prostatic tumour evolution, steps in metastatic spread and histogenomic associations revealed by integration of multi-region whole-genome sequencing with histopathological features.

BACKGROUND: Extension of prostate cancer beyond the primary site by local invasion or nodal metastasis is associated with poor prognosis. Despite significant research on tumour evolution in prostate cancer metastasis, the emergence and evolution of cancer clones at this early stage of expansion and spread are poorly understood. We aimed to delineate the routes of evolution and cancer spread within the prostate and to seminal vesicles and lymph nodes, linking these to histological features that are used in diagnostic risk stratification. METHODS: We performed whole-genome sequencing on 42 prostate cancer samples from the prostate, seminal vesicles and lymph nodes of five treatment-naive patients with locally advanced disease. We spatially mapped the clonal composition of cancer across the prostate and the routes of spread of cancer cells within the prostate and to seminal vesicles and lymph nodes in each individual by analysing a total of > 19,000 copy number corrected single nucleotide variants. RESULTS: In each patient, we identified sample locations corresponding to the earliest part of the malignancy. In patient 10, we mapped the spread of cancer from the apex of the prostate to the seminal vesicles and identified specific genomic changes associated with the transformation of adenocarcinoma to amphicrine morphology during this spread. Furthermore, we show that the lymph node metastases in this patient arose from specific cancer clones found at the base of the prostate and the seminal vesicles. In patient 15, we observed increased mutational burden, altered mutational signatures and histological changes associated with whole genome duplication. In all patients in whom histological heterogeneity was observed (4/5), we found that the distinct morphologies were located on separate branches of their respective evolutionary trees. CONCLUSIONS: Our results link histological transformation with specific genomic alterations and phylogenetic branching. These findings have implications for diagnosis and risk stratification, in addition to providing a rationale for further studies to characterise the genetic changes causally linked to morphological transformation. Our study demonstrates the value of integrating multi-region sequencing with histopathological data to understand tumour evolution and identify mechanisms of prostate cancer spread.

Spatial transcriptomic analysis of virtual prostate biopsy reveals confounding effect of tissue heterogeneity on genomic signatures.

Genetic signatures have added a molecular dimension to prognostics and therapeutic decision-making. However, tumour heterogeneity in prostate cancer and current sampling methods could confound accurate assessment. Based on previously published spatial transcriptomic data from multifocal prostate cancer, we created virtual biopsy models that mimic conventional biopsy placement and core size. We then analysed the gene expression of different prognostic signatures (OncotypeDx®, Decipher®, Prostadiag®) using a step-wise approach with increasing resolution from pseudo-bulk analysis of the whole biopsy, to differentiation by tissue subtype (benign, stroma, tumour), followed by distinct tumour grade and finally clonal resolution. The gene expression profile of virtual tumour biopsies revealed clear differences between grade groups and tumour clones, compared to a benign control, which were not reflected in bulk analyses. This suggests that bulk analyses of whole biopsies or tumour-only areas, as used in clinical practice, may provide an inaccurate assessment of gene profiles. The type of tissue, the grade of the tumour and the clonal composition all influence the gene expression in a biopsy. Clinical decision making based on biopsy genomics should be made with caution while we await more precise targeting and cost-effective spatial analyses.

Genomic Evolution and Transcriptional Changes in the Evolution of Prostate Cancer into Neuroendocrine and Ductal Carcinoma Types.

Prostate cancer is typically of acinar adenocarcinoma type but can occasionally present as neuroendocrine and/or ductal type carcinoma. These are associated with clinically aggressive disease, and the former often arises on a background of androgen deprivation therapy, although it can also arise de novo. Two prostate cancer cases were sequenced by exome capture from archival tissue. Case 1 was de novo small cell neuroendocrine carcinoma and ductal adenocarcinoma with three longitudinal samples over 5 years. Case 2 was a single time point after the development of treatment-related neuroendocrine prostate carcinoma. Case 1 showed whole genome doubling in all samples and focal amplification of AR in all samples except the first time point. Phylogenetic analysis revealed a common ancestry for ductal and small cell carcinoma. Case 2 showed 13q loss (involving RB1) in both adenocarcinoma and small cell carcinoma regions, and 3p gain, 4p loss, and 17p loss (involving TP53) in the latter. By using highly curated samples, we demonstrate for the first time that small-cell neuroendocrine and ductal prostatic carcinoma can have a common ancestry. We highlight whole genome doubling in a patient with prostate cancer relapse, reinforcing its poor prognostic nature.

Aligning germline and somatic mutations in prostate cancer. Are genetics changing practice?

OBJECTIVE: To review the current status of germline and somatic (tumour) genetic testing for prostate cancer (PCa), and its relevance for clinical practice. METHODS: A narrative synthesis of various molecular profiles related to their clinical context was carried out. Current guidelines for genetic testing and its feasibility in clinical practice were analysed. We report the main identified genetic sequencing results or functional genomic scores for PCa published in the literature or obtained from the French PROGENE study. RESULTS: The molecular alterations observed in PCa are mostly linked to disruption of the androgen receptor (AR) pathway or DNA repair deficiency. The main known germline mutations affect the BReast CAncer gene 2 (BRCA2) and homeobox B13 (HOXB13) genes, whereas AR and tumour protein p53 (TP53) are the genes with most frequent somatic alterations in tumours from men with metastatic PCa. Molecular tests are now available for detecting some of these germline or somatic alterations and sometimes recommended by guidelines, but their utilisation must combine rationality and feasibility. They can guide specific therapies, notably for the management of metastatic disease. Indeed, following androgen deprivation, targeted therapies for PCa currently include poly-(ADP-ribose)-polymerase (PARP) inhibitors, immune checkpoint inhibitors, and prostate-specific membrane antigen (PSMA)-guided radiotherapy. The genetic tests currently approved for targeted therapies remain limited to the detection of BRCA1 and BRCA2 mutation and DNA mismatch repair deficiency, while large panels are recommended for germline analyses, not only for inherited cancer predisposing syndrome, but also for metastatic PCa. CONCLUSIONS: Further consensus aligning germline with somatic molecular analysis in metastatic PCa is required, including genomics scars, emergent immunohistochemistry, or functional pre-screen imaging. With rapid advances in knowledge and technology in the field, continuous updating of guidelines to help the clinical management of these individuals, and well-conducted studies to evaluate the benefits of genetic testing are needed.

The architecture of clonal expansions in morphologically normal tissue from cancerous and non-cancerous prostates.

BACKGROUND: Up to 80% of cases of prostate cancer present with multifocal independent tumour lesions leading to the concept of a field effect present in the normal prostate predisposing to cancer development. In the present study we applied Whole Genome DNA Sequencing (WGS) to a group of morphologically normal tissue (n = 51), including benign prostatic hyperplasia (BPH) and non-BPH samples, from men with and men without prostate cancer. We assess whether the observed genetic changes in morphologically normal tissue are linked to the development of cancer in the prostate. RESULTS: Single nucleotide variants (P = 7.0 × 10-03, Wilcoxon rank sum test) and small insertions and deletions (indels, P = 8.7 × 10-06) were significantly higher in morphologically normal samples, including BPH, from men with prostate cancer compared to those without. The presence of subclonal expansions under selective pressure, supported by a high level of mutations, were significantly associated with samples from men with prostate cancer (P = 0.035, Fisher exact test). The clonal cell fraction of normal clones was always higher than the proportion of the prostate estimated as epithelial (P = 5.94 × 10-05, paired Wilcoxon signed rank test) which, along with analysis of primary fibroblasts prepared from BPH specimens, suggests a stromal origin. Constructed phylogenies revealed lineages associated with benign tissue that were completely distinct from adjacent tumour clones, but a common lineage between BPH and non-BPH morphologically normal tissues was often observed. Compared to tumours, normal samples have significantly less single nucleotide variants (P = 3.72 × 10-09, paired Wilcoxon signed rank test), have very few rearrangements and a complete lack of copy number alterations. CONCLUSIONS: Cells within regions of morphologically normal tissue (both BPH and non-BPH) can expand under selective pressure by mechanisms that are distinct from those occurring in adjacent cancer, but that are allied to the presence of cancer. Expansions, which are probably stromal in origin, are characterised by lack of recurrent driver mutations, by almost complete absence of structural variants/copy number alterations, and mutational processes similar to malignant tissue. Our findings have implications for treatment (focal therapy) and early detection approaches.

Spatially resolved clonal copy number alterations in benign and malignant tissue.

Defining the transition from benign to malignant tissue is fundamental to improving early diagnosis of cancer1. Here we use a systematic approach to study spatial genome integrity in situ and describe previously unidentified clonal relationships. We used spatially resolved transcriptomics2 to infer spatial copy number variations in >120,000 regions across multiple organs, in benign and malignant tissues. We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue using an organ-wide approach focused on the prostate. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. We highlight the power of capturing the molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms, including focal therapy.

Rare Germline Variants Are Associated with Rapid Biochemical Recurrence After Radical Prostate Cancer Treatment: A Pan Prostate Cancer Group Study.

BACKGROUND: Germline variants explain more than a third of prostate cancer (PrCa) risk, but very few associations have been identified between heritable factors and clinical progression. OBJECTIVE: To find rare germline variants that predict time to biochemical recurrence (BCR) after radical treatment in men with PrCa and understand the genetic factors associated with such progression. DESIGN, SETTING, AND PARTICIPANTS: Whole-genome sequencing data from blood DNA were analysed for 850 PrCa patients with radical treatment from the Pan Prostate Cancer Group (PPCG) consortium from the UK, Canada, Germany, Australia, and France. Findings were validated using 383 patients from The Cancer Genome Atlas (TCGA) dataset. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: A total of 15,822 rare (MAF <1%) predicted-deleterious coding germline mutations were identified. Optimal multifactor and univariate Cox regression models were built to predict time to BCR after radical treatment, using germline variants grouped by functionally annotated gene sets. Models were tested for robustness using bootstrap resampling. RESULTS AND LIMITATIONS: Optimal Cox regression multifactor models showed that rare predicted-deleterious germline variants in "Hallmark" gene sets were consistently associated with altered time to BCR. Three gene sets had a statistically significant association with risk-elevated outcome when modelling all samples: PI3K/AKT/mTOR, Inflammatory response, and KRAS signalling (up). PI3K/AKT/mTOR and KRAS signalling (up) were also associated among patients with higher-grade cancer, as were Pancreas-beta cells, TNFA signalling via NKFB, and Hypoxia, the latter of which was validated in the independent TCGA dataset. CONCLUSIONS: We demonstrate for the first time that rare deleterious coding germline variants robustly associate with time to BCR after radical treatment, including cohort-independent validation. Our findings suggest that germline testing at diagnosis could aid clinical decisions by stratifying patients for differential clinical management. PATIENT SUMMARY: Prostate cancer patients with particular genetic mutations have a higher chance of relapsing after initial radical treatment, potentially providing opportunities to identify patients who might need additional treatments earlier.

Subclone Eradication Analysis Identifies Targets for Enhanced Cancer Therapy and Reveals L1 Retrotransposition as a Dynamic Source of Cancer Heterogeneity.

Treatment-eradicated cancer subclones have been reported in leukemia and have recently been detected in solid tumors. Here we introduce Differential Subclone Eradication and Resistance (DSER) analysis, a method developed to identify molecular targets for improved therapy by direct comparison of genomic features of eradicated and resistant subclones in pre- and posttreatment samples from a patient with BRCA2-deficient metastatic prostate cancer. FANCI and EYA4 were identified as candidate DNA repair-related targets for converting subclones from resistant to eradicable, and RNAi-mediated depletion of FANCI confirmed it as a potential target. The EYA4 alteration was associated with adjacent L1 transposon insertion during cancer evolution upon treatment, raising questions surrounding the role of therapy in L1 activation. Both carboplatin and enzalutamide turned on L1 transposon machinery in LNCaP and VCaP but not in PC3 and 22Rv1 prostate cancer cell lines. L1 activation in LNCaP and VCaP was inhibited by the antiretroviral drug azidothymidine. L1 activation was also detected postcastration in LuCaP 77 and LuCaP 105 xenograft models and postchemotherapy in previously published time-series transcriptomic data from SCC25 head and neck cancer cells. In conclusion, DSER provides an informative intermediate step toward effective precision cancer medicine and should be tested in future studies, especially those including dramatic but temporary metastatic tumor regression. L1 transposon activation may be a modifiable source of cancer genomic heterogeneity, suggesting the potential of leveraging newly discovered triggers and blockers of L1 activity to overcome therapy resistance. SIGNIFICANCE: Differential analysis of eradicated and resistant subclones following cancer treatment identifies that L1 activity associated with resistance is induced by current therapies and blocked by the antiretroviral drug azidothymidine.

A Systematic Review of Prostate Cancer Heterogeneity: Understanding the Clonal Ancestry of Multifocal Disease.

CONTEXT: Studies characterising genomic changes in prostate cancer (PCa) during natural progression have greatly increased our understanding of the disease. A better understanding of the evolutionary history of PCa would allow advances in diagnostics, prognostication, and novel therapies that together will improve patient outcomes. OBJECTIVE: To review the molecular heterogeneity of PCa and assess recent efforts to profile intratumoural heterogeneity and clonal evolution. EVIDENCE ACQUISITION: We screened a total of 1313 abstracts from PubMed published between 2009 and 2020, of which we reviewed 84 full-text articles. We excluded 49, resulting in 35 studies for qualitative analysis. EVIDENCE SYNTHESIS: In studies of primary disease (16 studies, 4793 specimens), there is a lack of consensus regarding the monoclonal or polyclonal origin of primary PCa. There is no consistent mutation giving rise to primary PCa. Detailed clonal analysis of primary PCa has been limited by current techniques. By contrast, clonal relationships between PCa metastases and a potentiating clone have been consistently identified (19 studies, 732 specimens). Metastatic specimens demonstrate consistent truncal genomic aberrations that suggest monoclonal metastatic progenitors. CONCLUSIONS: The relationship between the clonal dynamics of PCa and clinical outcomes needs further investigation. It is likely that this will provide a biological rationale for whether radical treatment of the primary tumour benefits patients with oligometastatic PCa. Future studies on the mutational burden in primary disease at single-cell resolution should permit the identification of clonal patterns underpinning the origin of lethal PCa. PATIENT SUMMARY: Prostate cancers arise in different parts of the prostate because of DNA mutations that occur by chance at different times. These cancer cells and their origin can be tracked by DNA mapping. In this review we summarise the state of the art and outline what further science is needed to provide the missing answers.

Genomic copy number predicts esophageal cancer years before transformation.

Recent studies show that aneuploidy and driver gene mutations precede cancer diagnosis by many years1-4. We assess whether these genomic signals can be used for early detection and pre-emptive cancer treatment using the neoplastic precursor lesion Barrett's esophagus as an exemplar5. Shallow whole-genome sequencing of 777 biopsies, sampled from 88 patients in Barrett's esophagus surveillance over a period of up to 15 years, shows that genomic signals can distinguish progressive from stable disease even 10 years before histopathological transformation. These findings are validated on two independent cohorts of 76 and 248 patients. These methods are low-cost and applicable to standard clinical biopsy samples. Compared with current management guidelines based on histopathology and clinical presentation, genomic classification enables earlier treatment for high-risk patients as well as reduction of unnecessary treatment and monitoring for patients who are unlikely to develop cancer.

Multiplexing information flow through dynamic signalling systems.

We consider how a signalling system can act as an information hub by multiplexing information arising from multiple signals. We formally define multiplexing, mathematically characterise which systems can multiplex and how well they can do it. While the results of this paper are theoretical, to motivate the idea of multiplexing, we provide experimental evidence that tentatively suggests that the NF-κB transcription factor can multiplex information about changes in multiple signals. We believe that our theoretical results may resolve the apparent paradox of how a system like NF-κB that regulates cell fate and inflammatory signalling in response to diverse stimuli can appear to have the low information carrying capacity suggested by recent studies on scalar signals. In carrying out our study, we introduce new methods for the analysis of large, nonlinear stochastic dynamic models, and develop computational algorithms that facilitate the calculation of fundamental constructs of information theory such as Kullback-Leibler divergences and sensitivity matrices, and link these methods to a new theory about multiplexing information. We show that many current models such as those of the NF-κB system cannot multiplex effectively and provide models that overcome this limitation using post-transcriptional modifications.

The evolutionary landscape of colorectal tumorigenesis.

The evolutionary events that cause colorectal adenomas (benign) to progress to carcinomas (malignant) remain largely undetermined. Using multi-region genome and exome sequencing of 24 benign and malignant colorectal tumours, we investigate the evolutionary fitness landscape occupied by these neoplasms. Unlike carcinomas, advanced adenomas frequently harbour sub-clonal driver mutations-considered to be functionally important in the carcinogenic process-that have not swept to fixation, and have relatively high genetic heterogeneity. Carcinomas are distinguished from adenomas by widespread aneusomies that are usually clonal and often accrue in a 'punctuated' fashion. We conclude that adenomas evolve across an undulating fitness landscape, whereas carcinomas occupy a sharper fitness peak, probably owing to stabilizing selection.

Sequencing of prostate cancers identifies new cancer genes, routes of progression and drug targets.

Prostate cancer represents a substantial clinical challenge because it is difficult to predict outcome and advanced disease is often fatal. We sequenced the whole genomes of 112 primary and metastatic prostate cancer samples. From joint analysis of these cancers with those from previous studies (930 cancers in total), we found evidence for 22 previously unidentified putative driver genes harboring coding mutations, as well as evidence for NEAT1 and FOXA1 acting as drivers through noncoding mutations. Through the temporal dissection of aberrations, we identified driver mutations specifically associated with steps in the progression of prostate cancer, establishing, for example, loss of CHD1 and BRCA2 as early events in cancer development of ETS fusion-negative cancers. Computational chemogenomic (canSAR) analysis of prostate cancer mutations identified 11 targets of approved drugs, 7 targets of investigational drugs, and 62 targets of compounds that may be active and should be considered candidates for future clinical trials.

The long non-coding RNA Paupar promotes KAP1-dependent chromatin changes and regulates olfactory bulb neurogenesis.

Many long non-coding RNAs (lncRNAs) are expressed during central nervous system (CNS) development, yet their in vivo roles and mechanisms of action remain poorly understood. Paupar, a CNS-expressed lncRNA, controls neuroblastoma cell growth by binding and modulating the activity of transcriptional regulatory elements in a genome-wide manner. We show here that the Paupar lncRNA directly binds KAP1, an essential epigenetic regulatory protein, and thereby regulates the expression of shared target genes important for proliferation and neuronal differentiation. Paupar promotes KAP1 chromatin occupancy and H3K9me3 deposition at a subset of distal targets, through the formation of a ribonucleoprotein complex containing Paupar, KAP1 and the PAX6 transcription factor. Paupar-KAP1 genome-wide co-occupancy reveals a fourfold enrichment of overlap between Paupar and KAP1 bound sequences, the majority of which also appear to associate with PAX6. Furthermore, both Paupar and Kap1 loss-of-function in vivo disrupt olfactory bulb neurogenesis. These observations provide important conceptual insights into the trans-acting modes of lncRNA-mediated epigenetic regulation and the mechanisms of KAP1 genomic recruitment, and identify Paupar and Kap1 as regulators of neurogenesis in vivo.

Lineage-specific plasmid acquisition and the evolution of specialized pathogens in Bacillus thuringiensis and the Bacillus cereus group.

Bacterial plasmids can vary from small selfish genetic elements to large autonomous replicons that constitute a significant proportion of total cellular DNA. By conferring novel function to the cell, plasmids may facilitate evolution but their mobility may be opposed by co-evolutionary relationships with chromosomes or encouraged via the infectious sharing of genes encoding public goods. Here, we explore these hypotheses through large-scale examination of the association between plasmids and chromosomal DNA in the phenotypically diverse Bacillus cereus group. This complex group is rich in plasmids, many of which encode essential virulence factors (Cry toxins) that are known public goods. We characterized population genomic structure, gene content and plasmid distribution to investigate the role of mobile elements in diversification. We analysed coding sequence within the core and accessory genome of 190 B. cereus group isolates, including 23 novel sequences and genes from 410 reference plasmid genomes. While cry genes were widely distributed, those with invertebrate toxicity were predominantly associated with one sequence cluster (clade 2) and phenotypically defined Bacillus thuringiensis. Cry toxin plasmids in clade 2 showed evidence of recent horizontal transfer and variable gene content, a pattern of plasmid segregation consistent with transfer during infectious cooperation. Nevertheless, comparison between clades suggests that co-evolutionary interactions may drive association between plasmids and chromosomes and limit wider transfer of key virulence traits. Proliferation of successful plasmid and chromosome combinations is a feature of specialized pathogens with characteristic niches (Bacillus anthracis, B. thuringiensis) and has occurred multiple times in the B. cereus group.

Genomic plasticity and rapid host switching can promote the evolution of generalism: a case study in the zoonotic pathogen Campylobacter.

Horizontal gene transfer accelerates bacterial adaptation to novel environments, allowing selection to act on genes that have evolved in multiple genetic backgrounds. This can lead to ecological specialization. However, little is known about how zoonotic bacteria maintain the ability to colonize multiple hosts whilst competing with specialists in the same niche. Here we develop a stochastic evolutionary model and show how genetic transfer of host segregating alleles, distributed as predicted for niche specifying genes, and the opportunity for host transition could interact to promote the emergence of host generalist lineages of the zoonotic bacterium Campylobacter. Using a modelling approach we show that increasing levels of homologous recombination enhance the efficiency with which selection can fix combinations of beneficial alleles, speeding adaptation. We then show how these predictions change in a multi-host system, with low levels of recombination, consistent with real r/m estimates, increasing the standing variation in the population, allowing a more effective response to changes in the selective landscape. Our analysis explains how observed gradients of host specialism and generalism can evolve in a multihost system through the transfer of ecologically important loci among coexisting strains.

Conserved Cis-Regulatory Modules Control Robustness in Msx1 Expression at Single-Cell Resolution.

The process of transcription is highly stochastic leading to cell-to-cell variations and noise in gene expression levels. However, key essential genes have to be precisely expressed at the correct amount and time to ensure proper cellular development and function. Studies in yeast and bacterial systems have shown that gene expression noise decreases as mean expression levels increase, a relationship that is controlled by promoter DNA sequence. However, the function of distal cis-regulatory modules (CRMs), an evolutionary novelty of metazoans, in controlling transcriptional robustness and variability is poorly understood. In this study, we used live cell imaging of transfected reporters combined with a mathematical modelling and statistical inference scheme to quantify the function of conserved Msx1 CRMs and promoters in modulating single-cell real-time transcription rates in C2C12 mouse myoblasts. The results show that the mean expression-noise relationship is solely promoter controlled for this key pluripotency regulator. In addition, we demonstrate that CRMs modulate single-cell basal promoter rate distributions in a graded manner across a population of cells. This extends the rheostatic model of CRM action to provide a more detailed understanding of CRM function at single-cell resolution. We also identify a novel CRM transcriptional filter function that acts to reduce intracellular variability in transcription rates and show that this can be phylogenetically separable from rate modulating CRM activities. These results are important for understanding how the expression of key vertebrate developmental transcription factors is precisely controlled both within and between individual cells.

A hierarchical model of transcriptional dynamics allows robust estimation of transcription rates in populations of single cells with variable gene copy number.

MOTIVATION: cis-regulatory DNA sequence elements, such as enhancers and silencers, function to control the spatial and temporal expression of their target genes. Although the overall levels of gene expression in large cell populations seem to be precisely controlled, transcription of individual genes in single cells is extremely variable in real time. It is, therefore, important to understand how these cis-regulatory elements function to dynamically control transcription at single-cell resolution. Recently, statistical methods have been proposed to back calculate the rates involved in mRNA transcription using parameter estimation of a mathematical model of transcription and translation. However, a major complication in these approaches is that some of the parameters, particularly those corresponding to the gene copy number and transcription rate, cannot be distinguished; therefore, these methods cannot be used when the copy number is unknown. RESULTS: Here, we develop a hierarchical Bayesian model to estimate biokinetic parameters from live cell enhancer-promoter reporter measurements performed on a population of single cells. This allows us to investigate transcriptional dynamics when the copy number is variable across the population. We validate our method using synthetic data and then apply it to quantify the function of two known developmental enhancers in real time and in single cells. AVAILABILITY: Supporting information is submitted with the article.

Evidence for phenotypic plasticity among multihost Campylobacter jejuni and C. coli lineages, obtained using ribosomal multilocus sequence typing and Raman spectroscopy.

Closely related bacterial isolates can display divergent phenotypes. This can limit the usefulness of phylogenetic studies for understanding bacterial ecology and evolution. Here, we compare phenotyping based on Raman spectrometric analysis of cellular composition to phylogenetic classification by ribosomal multilocus sequence typing (rMLST) in 108 isolates of the zoonotic pathogens Campylobacter jejuni and C. coli. Automatic relevance determination (ARD) was used to identify informative peaks in the Raman spectra that could be used to distinguish strains in taxonomic and host source groups (species, clade, clonal complex, and isolate source/host). Phenotypic characterization based on Raman spectra showed a degree of agreement with genotypic classification using rMLST, with segregation accuracy between species (83.95%), clade (in C. coli, 98.41%), and, to some extent, clonal complex (86.89% C. jejuni ST-21 and ST-45 complexes) being achieved. This confirmed the utility of Raman spectroscopy for lineage classification and the correlation between genotypic and phenotypic classification. In parallel analysis, relatively distantly related isolates (different clonal complexes) were assigned the correct host origin irrespective of the clonal origin (74.07 to 96.97% accuracy) based upon different Raman peaks. This suggests that the phenotypic characteristics, from which the phenotypic signal is derived, are not fixed by clonal descent but are influenced by the host environment and change as strains move between hosts.