Molecular specificity, convergence and constraint shape adaptive evolution in nutrient-poor environments.

One of the central goals of evolutionary biology is to explain and predict the molecular basis of adaptive evolution. We studied the evolution of genetic networks in Saccharomyces cerevisiae (budding yeast) populations propagated for more than 200 generations in different nitrogen-limiting conditions. We find that rapid adaptive evolution in nitrogen-poor environments is dominated by the de novo generation and selection of copy number variants (CNVs), a large fraction of which contain genes encoding specific nitrogen transporters including PUT4, DUR3 and DAL4. The large fitness increases associated with these alleles limits the genetic heterogeneity of adapting populations even in environments with multiple nitrogen sources. Complete identification of acquired point mutations, in individual lineages and entire populations, identified heterogeneity at the level of genetic loci but common themes at the level of functional modules, including genes controlling phosphatidylinositol-3-phosphate metabolism and vacuole biogenesis. Adaptive strategies shared with other nutrient-limited environments point to selection of genetic variation in the TORC1 and Ras/PKA signaling pathways as a general mechanism underlying improved growth in nutrient-limited environments. Within a single population we observed the repeated independent selection of a multi-locus genotype, comprised of the functionally related genes GAT1, MEP2 and LST4. By studying the fitness of individual alleles, and their combination, as well as the evolutionary history of the evolving population, we find that the order in which these mutations are acquired is constrained by epistasis. The identification of repeatedly selected variation at functionally related loci that interact epistatically suggests that gene network polymorphisms (GNPs) may be a frequent outcome of adaptive evolution. Our results provide insight into the mechanistic basis by which cells adapt to nutrient-limited environments and suggest that knowledge of the selective environment and the regulatory mechanisms important for growth and survival in that environment greatly increase the predictability of adaptive evolution.

Application of high-throughput single-nucleus DNA sequencing in pancreatic cancer.

Despite insights gained by bulk DNA sequencing of cancer it remains challenging to resolve the admixture of normal and tumor cells, and/or of distinct tumor subclones; high-throughput single-cell DNA sequencing circumvents these and brings cancer genomic studies to higher resolution. However, its application has been limited to liquid tumors or a small batch of solid tumors, mainly because of the lack of a scalable workflow to process solid tumor samples. Here we optimize a highly automated nuclei extraction workflow that achieves fast and reliable targeted single-nucleus DNA library preparation of 38 samples from 16 pancreatic ductal adenocarcinoma patients, with an average library yield per sample of 2867 single nuclei. We demonstrate that this workflow not only performs well using low cellularity or low tumor purity samples but reveals genomic evolution patterns of pancreatic ductal adenocarcinoma as well.

Cancer cells co-evolve with retrotransposons to mitigate viral mimicry.

Overexpression of repetitive elements is an emerging hallmark of human cancers 1 . Diverse repeats can mimic viruses by replicating within the cancer genome through retrotransposition, or presenting pathogen-associated molecular patterns (PAMPs) to the pattern recognition receptors (PRRs) of the innate immune system 2-5 . Yet, how specific repeats affect tumor evolution and shape the tumor immune microenvironment (TME) in a pro- or anti-tumorigenic manner remains poorly defined. Here, we integrate whole genome and total transcriptome data from a unique autopsy cohort of multiregional samples collected in pancreatic ductal adenocarcinoma (PDAC) patients, into a comprehensive evolutionary analysis. We find that more recently evolved S hort I nterspersed N uclear E lements (SINE), a family of retrotransposable repeats, are more likely to form immunostimulatory double-strand RNAs (dsRNAs). Consequently, younger SINEs are strongly co-regulated with RIG-I like receptor associated type-I interferon genes but anti-correlated with pro-tumorigenic macrophage infiltration. We discover that immunostimulatory SINE expression in tumors is regulated by either L ong I nterspersed N uclear E lements 1 (LINE1/L1) mobility or ADAR1 activity in a TP53 mutation dependent manner. Moreover, L1 retrotransposition activity tracks with tumor evolution and is associated with TP53 mutation status. Altogether, our results suggest pancreatic tumors actively evolve to modulate immunogenic SINE stress and induce pro-tumorigenic inflammation. Our integrative, evolutionary analysis therefore illustrates, for the first time, how dark matter genomic repeats enable tumors to co-evolve with the TME by actively regulating viral mimicry to their selective advantage.

The pancreatic cancer genome revisited.

Pancreatic cancer is a genetic disease, and the recurrent genetic alterations characteristic of pancreatic cancer indicate the cellular processes that are targeted for malignant transformation. In addition to somatic alterations in the most common driver genes (KRAS, CDKN2A, TP53 and SMAD4), large-scale studies have revealed major roles for genetic alterations of the SWI/SNF and COMPASS complexes, copy number alterations in GATA6 and MYC that partially define phenotypes of pancreatic cancer, and the role(s) of polyploidy and chromothripsis as factors contributing to pancreatic cancer biology and progression. Germline variants that increase the risk of pancreatic cancer continue to be discovered along with a greater appreciation of the features of pancreatic cancers with mismatch repair deficiencies and homologous recombination deficiencies that confer sensitivity to therapeutic targeting. Wild-type KRAS pancreatic cancers, some of which are driven by alternative oncogenic events affecting NRG1 or NTRK1 - for which targeted therapies exist - further underscore that pancreatic cancer is formally entering the era of precision medicine. Given the vast developments within this field, here we review the wide-ranging and most current information related to pancreatic cancer genomics with the goal of integrating this information into a unifying description of the life history of pancreatic cancer.

The Genetic Evolution of Treatment-Resistant Cutaneous, Acral, and Uveal Melanomas.

PURPOSE: Melanoma is a biologically heterogeneous disease composed of distinct clinicopathologic subtypes that frequently resist treatment. To explore the evolution of treatment resistance and metastasis, we used a combination of temporal and multilesional tumor sampling in conjunction with whole-exome sequencing of 110 tumors collected from 7 patients with cutaneous (n = 3), uveal (n = 2), and acral (n = 2) melanoma subtypes. EXPERIMENTAL DESIGN: Primary tumors, metastases collected longitudinally, and autopsy tissues were interrogated. All but 1 patient died because of melanoma progression. RESULTS: For each patient, we generated phylogenies and quantified the extent of genetic diversity among tumors, specifically among putative somatic alterations affecting therapeutic resistance. CONCLUSIONS: In 4 patients who received immunotherapy, we found 1-3 putative acquired and intrinsic resistance mechanisms coexisting in the same patient, including mechanisms that were shared by all tumors within each patient, suggesting that future therapies directed at overcoming intrinsic resistance mechanisms may be broadly effective.

Construction of a functional network for common DNA damage responses in Escherichia coli.

In this study, we aim to identify a common, general mode of toxic action in Escherichia coli when experiencing DNA damage, irrespective of the agents used. We conducted or collected 69 microarray data from seven different DNA damaging agents. In a quantitative manner, we constructed a probable DNA damage stress network, entitled the 'Functional Linked Network (FLN)', which consists of 399 significantly perturbed genes and the 1283 interactions among them. The SOS response related genes (LexA modules) were found to be dominantly activated by DNA damage, irrespective of the agents. Several minor, plausible modules were also implicated in this network, and appear to be related with the metabolic inhibition response to DNA damage or mediate the induction of SOS response. This systems and comparison approach across a variety of genotoxic agents may serve as a starting point to specify some of the unknown and common features of DNA damage responses in bacteria.

A unifying paradigm for transcriptional heterogeneity and squamous features in pancreatic ductal adenocarcinoma.

Pancreatic cancer expression profiles largely reflect a classical or basal-like phenotype. The extent to which these profiles vary within a patient is unknown. We integrated evolutionary analysis and expression profiling in multiregion-sampled metastatic pancreatic cancers, finding that squamous features are the histologic correlate of an RNA-seq-defined basal-like subtype. In patients with coexisting basal and squamous and classical and glandular morphology, phylogenetic studies revealed that squamous morphology represented a subclonal population in an otherwise classical and glandular tumor. Cancers with squamous features were significantly more likely to have clonal mutations in chromatin modifiers, intercellular heterogeneity for MYC amplification and entosis. These data provide a unifying paradigm for integrating basal-type expression profiles, squamous histology and somatic mutations in chromatin modifier genes in the context of clonal evolution of pancreatic cancer.

The Evolutionary Origins of Recurrent Pancreatic Cancer.

Surgery is the only curative option for stage I/II pancreatic cancer; nonetheless, most patients will experience a recurrence after surgery and die of their disease. To identify novel opportunities for management of recurrent pancreatic cancer, we performed whole-exome or targeted sequencing of 10 resected primary cancers and matched intrapancreatic recurrences or distant metastases. We identified that recurrent disease after adjuvant or first-line platinum therapy corresponds to an increased mutational burden. Recurrent disease is enriched for genetic alterations predicted to activate MAPK/ERK and PI3K-AKT signaling and develops from a monophyletic or polyphyletic origin. Treatment-induced genetic bottlenecks lead to a modified genetic landscape and subclonal heterogeneity for driver gene alterations in part due to intermetastatic seeding. In 1 patient what was believed to be recurrent disease was an independent (second) primary tumor. These findings suggest routine post-treatment sampling may have value in the management of recurrent pancreatic cancer. SIGNIFICANCE: The biological features or clinical vulnerabilities of recurrent pancreatic cancer after pancreaticoduodenectomy are unknown. Using whole-exome sequencing we find that recurrent disease has a distinct genomic landscape, intermetastatic genetic heterogeneity, diverse clonal origins, and higher mutational burden than found for treatment-naïve disease.See related commentary by Bednar and Pasca di Magliano, p. 762.This article is highlighted in the In This Issue feature, p. 747.

An incoherent feedforward loop facilitates adaptive tuning of gene expression.

We studied adaptive evolution of gene expression using long-term experimental evolution of Saccharomyces cerevisiae in ammonium-limited chemostats. We found repeated selection for non-synonymous variation in the DNA binding domain of the transcriptional activator, GAT1, which functions with the repressor, DAL80 in an incoherent type-1 feedforward loop (I1-FFL) to control expression of the high affinity ammonium transporter gene, MEP2. Missense mutations in the DNA binding domain of GAT1 reduce its binding to the GATAA consensus sequence. However, we show experimentally, and using mathematical modeling, that decreases in GAT1 binding result in increased expression of MEP2 as a consequence of properties of I1-FFLs. Our results show that I1-FFLs, one of the most commonly occurring network motifs in transcriptional networks, can facilitate adaptive tuning of gene expression through modulation of transcription factor binding affinities. Our findings highlight the importance of gene regulatory architectures in the evolution of gene expression.

Incorporation of unique molecular identifiers in TruSeq adapters improves the accuracy of quantitative sequencing.

Quantitative analysis of next-generation sequencing (NGS) data requires discriminating duplicate reads generated by PCR from identical molecules that are of unique origin. Typically, PCR duplicates are identified as sequence reads that align to the same genomic coordinates using reference-based alignment. However, identical molecules can be independently generated during library preparation. Misidentification of these molecules as PCR duplicates can introduce unforeseen biases during analyses. Here, we developed a cost-effective sequencing adapter design by modifying Illumina TruSeq adapters to incorporate a unique molecular identifier (UMI) while maintaining the capacity to undertake multiplexed, single-index sequencing. Incorporation of UMIs into TruSeq adapters (TrUMIseq adapters) enables identification of bona fide PCR duplicates as identically mapped reads with identical UMIs. Using TrUMIseq adapters, we show that accurate removal of PCR duplicates results in improved accuracy of both allele frequency (AF) estimation in heterogeneous populations using DNA sequencing and gene expression quantification using RNA-Seq.

Limited heterogeneity of known driver gene mutations among the metastases of individual patients with pancreatic cancer.

The extent of heterogeneity among driver gene mutations present in naturally occurring metastases-that is, treatment-naive metastatic disease-is largely unknown. To address this issue, we carried out 60× whole-genome sequencing of 26 metastases from four patients with pancreatic cancer. We found that identical mutations in known driver genes were present in every metastatic lesion for each patient studied. Passenger gene mutations, which do not have known or predicted functional consequences, accounted for all intratumoral heterogeneity. Even with respect to these passenger mutations, our analysis suggests that the genetic similarity among the founding cells of metastases was higher than that expected for any two cells randomly taken from a normal tissue. The uniformity of known driver gene mutations among metastases in the same patient has critical and encouraging implications for the success of future targeted therapies in advanced-stage disease.

Electrochemical possibility of iron compounds in used disposable heating pads and their use in lithium ion batteries.

In this study, iron oxides obtained from used disposable heating pads are used as an anode material in lithium ion batteries. Fe3O4 and Fe2O3 phases are identified using XRD. Additionally, the existence of other substances, such as carbon and NaCl, are determined using EDS dot mapping. Purified powder (PP) is prepared by washing the obtained powder (OP) with distilled water and ethanol. Heat-treated powder (HP) is prepared by heating PP at 600 °C. The electrochemical result shows that PP delivers a discharge capacity of ∼700 mAh g(-1) after 50 cycles. HP delivers a higher initial capacity of 1170 mAh g(-1); however, the discharge capacity decreases drastically to 500 mAh g(-1). These results were similar to those determined for commercial iron oxide in previous studies.

The functional basis of adaptive evolution in chemostats.

Two of the central problems in biology are determining the molecular basis of adaptive evolution and understanding how cells regulate their growth. The chemostat is a device for culturing cells that provides great utility in tackling both of these problems: it enables precise control of the selective pressure under which organisms evolve and it facilitates experimental control of cell growth rate. The aim of this review is to synthesize results from studies of the functional basis of adaptive evolution in long-term chemostat selections using Escherichia coli and Saccharomyces cerevisiae. We describe the principle of the chemostat, provide a summary of studies of experimental evolution in chemostats, and use these studies to assess our current understanding of selection in the chemostat. Functional studies of adaptive evolution in chemostats provide a unique means of interrogating the genetic networks that control cell growth, which complements functional genomic approaches and quantitative trait loci (QTL) mapping in natural populations. An integrated approach to the study of adaptive evolution that accounts for both molecular function and evolutionary processes is critical to advancing our understanding of evolution. By renewing efforts to integrate these two research programs, experimental evolution in chemostats is ideally suited to extending the functional synthesis to the study of genetic networks.