ACSM1 and ACSM3 Regulate Fatty Acid Metabolism to Support Prostate Cancer Growth and Constrain Ferroptosis.

Solid tumors are highly reliant on lipids for energy, growth, and survival. In prostate cancer, the activity of the androgen receptor (AR) is associated with reprogramming of lipid metabolic processes. Here, we identified acyl-CoA synthetase medium chain family members 1 and 3 (ACSM1 and ACSM3) as AR-regulated mediators of prostate cancer metabolism and growth. ACSM1 and ACSM3 were upregulated in prostate tumors compared with nonmalignant tissues and other cancer types. Both enzymes enhanced proliferation and protected prostate cancer cells from death in vitro, whereas silencing ACSM3 led to reduced tumor growth in an orthotopic xenograft model. ACSM1 and ACSM3 were major regulators of the prostate cancer lipidome and enhanced energy production via fatty acid oxidation. Metabolic dysregulation caused by loss of ACSM1/3 led to mitochondrial oxidative stress, lipid peroxidation, and cell death by ferroptosis. Conversely, elevated ACSM1/3 activity enabled prostate cancer cells to survive toxic levels of medium chain fatty acids and promoted resistance to ferroptosis-inducing drugs and AR antagonists. Collectively, this study reveals a tumor-promoting function of medium chain acyl-CoA synthetases and positions ACSM1 and ACSM3 as key players in prostate cancer progression and therapy resistance. Significance: Androgen receptor-induced ACSM1 and ACSM3 mediate a metabolic pathway in prostate cancer that enables the utilization of medium chain fatty acids for energy production, blocks ferroptosis, and drives resistance to clinically approved antiandrogens.

Potent Stimulation of the Androgen Receptor Instigates a Viral Mimicry Response in Prostate Cancer.

Inhibiting the androgen receptor (AR), a ligand-activated transcription factor, with androgen deprivation therapy is a standard-of-care treatment for metastatic prostate cancer. Paradoxically, activation of AR can also inhibit the growth of prostate cancer in some patients and experimental systems, but the mechanisms underlying this phenomenon are poorly understood. This study exploited a potent synthetic androgen, methyltestosterone (MeT), to investigate AR agonist-induced growth inhibition. MeT strongly inhibited growth of prostate cancer cells expressing AR, but not AR-negative models. Genes and pathways regulated by MeT were highly analogous to those regulated by DHT, although MeT induced a quantitatively greater androgenic response in prostate cancer cells. MeT potently downregulated DNA methyltransferases, leading to global DNA hypomethylation. These epigenomic changes were associated with dysregulation of transposable element expression, including upregulation of endogenous retrovirus (ERV) transcripts after sustained MeT treatment. Increased ERV expression led to accumulation of double-stranded RNA and a "viral mimicry" response characterized by activation of IFN signaling, upregulation of MHC class I molecules, and enhanced recognition of murine prostate cancer cells by CD8+ T cells. Positive associations between AR activity and ERVs/antiviral pathways were evident in patient transcriptomic data, supporting the clinical relevance of our findings. Collectively, our study reveals that the potent androgen MeT can increase the immunogenicity of prostate cancer cells via a viral mimicry response, a finding that has potential implications for the development of strategies to sensitize this cancer type to immunotherapies. Significance: Our study demonstrates that potent androgen stimulation of prostate cancer cells can elicit a viral mimicry response, resulting in enhanced IFN signaling. This finding may have implications for the development of strategies to sensitize prostate cancer to immunotherapies.

An interdependence between GAPVD1 gene polymorphism, expression level and response to interferon beta in patients with multiple sclerosis.

Interferon-ß (IFN-ß) is among the first drugs used for reducing the symptoms of multiple sclerosis (MS). Many studies show that the genetic predisposition of patients might modulate their response to IFN-ß treatment. In this study GAPVD1 gene expression and the genotyping of rs2291858 variant were analysed in 100 responder and 100 non-responder patients with MS treated using IFN-ß. Moreover, rs2291858 genotyping was performed for 200 patients with MS and 200 healthy controls. GAPVD1 expression was significantly increased in the responder patients than in non-responders and the distribution of rs2291858 polymorphism was significantly different between them. The GAPVD1 expression level in AA genotype of the responder group was higher than that in other genotypes of these two groups. The results show that the GAPVD1 expression level and rs2291858 genotype probably affect the response to IFN- ß in patients with MS.

State-of-the-Art and Trends in Synthesis, Properties, and Application of Quantum Dots-Based Nanomaterials.

Quantum dots (QDs) with a nanoscale size range have attracted significant attention in various areas of nanotechnology due to their unique properties. Different strategies for the synthesis of QD nanoparticles are reported in which various factors, such as size, impurities, shape, and crystallinity, affect the QDs fundamental properties. Consequently, to obtain QDs with appropriate physical properties, it is required to select a synthesis method which allows enough control over the surface chemistry of QDs through fine-tuning of the synthesis parameters. Moreover, QDs nanocrystals are recently used in multidisciplinary research integrated with biological interfaces. The state-of-the-art methods for synthesizing QDs and bioconjugation strategies to provide insight into various applications of these nanomaterials are discussed herein.

The hypothetical roles of arsenic in multiple sclerosis by induction of inflammation and aggregation of tau protein: A commentary.

Multiple sclerosis (MS) is a disease which manifests demyelination of neuronal cells in the brain. Despite extensive research on the mechanisms of disease development and progression, the exact mechanism is not elucidated yet, which has hampered drug development and subsequent treatment of the disease. We have recently shown that the serum levels of arsenic and malondialdehyde, a lipid peroxidation marker, are high in MS patients. In this article, we would like to formulate the hypothesis that arsenic may cause MS by induction of inflammation, degeneration, and apoptosis in neuronal cells. The induction of ROS generation in cells upon exposure to arsenic as a heavy metal may be involved in the pathogenesis of MS. Tau protein, a member of the family of microtubule-associated proteins, is mainly expressed in neurons and contribute to the assembly of neuronal microtubules network. Arsenic may affect the hyperphosphorylation and aggregation of tau proteins and may be involved in the cascade leading to deregulation of tau function associated with neurodegeneration. For validation of this hypothesis, studies might be conducted to evaluate the association of arsenic levels and tau protein levels in MS patients. Further studies might also focus on the trafficking along microtubules in neurons of MS patient with regard to hyperphosphorylation of tau protein. This hypothesis may add a new dimension to the understanding of MS etiology and help to design novel therapeutic agents against potential targets that might be discovered. If this hypothesis proves to be true, tau phosphorylation inhibitors can be potential candidates for MS drug development.

Recent advances on biomedical applications of scaffolds in wound healing and dermal tissue engineering.

The tissue engineering field has developed in response to the shortcomings related to the replacement of the tissues lost to disease or trauma: donor tissue rejection, chronic inflammation and donor tissue shortages. The driving force behind the tissue engineering is to avoid the mentioned issues by creating the biological substitutes capable of replacing the damaged tissue. This is done by combining the scaffolds, cells and signals in order to create the living, physiological, three-dimensional tissues. A wide variety of skin substitutes are used in the treatment of full-thickness injuries. Substitutes made from skin can harbour the latent viruses, and artificial skin grafts can heal with the extensive scarring, failing to regenerate structures such as glands, nerves and hair follicles. New and practical skin scaffold materials remain to be developed. The current article describes the important information about wound healing scaffolds. The scaffold types which were used in these fields were classified according to the accepted guideline of the biological medicine. Moreover, the present article gave the brief overview on the fundamentals of the tissue engineering, biodegradable polymer properties and their application in skin wound healing. Also, the present review discusses the type of the tissue engineered skin substitutes and modern wound dressings which promote the wound healing.

Development of quantum-dot-encapsulated liposome-based optical nanobiosensor for detection of telomerase activity without target amplification.

Reactivation of telomerase, which is observed in more than 85% of all known human tumours, is considered a promising tumour marker for cancer diagnosis. With respect to the biomedical importance of telomerase, we have developed a simple strategy based on liposomal fluorescent signal amplification for highly sensitive optical detection of telomerase activity using liposome-encapsulated cadmium telluride quantum dots. In this strategy, telomerase extracted from A549 cells elongated the biotinylated telomerase substrate primer, which was then immobilized on streptavidine-coated microplate wells. After the hybridization of the telomerase-elongated product with biotinylated capture probe, streptavidin was added to the assembly. In the next step, biotinylated liposome was conjugated with capture probe through streptavidin. Finally, QD-encapsulated liposomes were disrupted by Triton X-100, and the fluorescence intensity of the released QDs was measured to detect telomerase activity. The results showed that the proposed nanobiosensor was able to detect telomerase activity from as few as 10 A549 cells without the enzymatic amplification of telomerase extension products. In short, this method is not only convenient and sensitive, but also has a simple operating protocol and a wide detection range (10-5000 cells). A linear range was observed between 50 and 800 cells with a correlation coefficient of 0.982 and regression equation of y = 0.0444 x + 17.137. The proposed method is economical, more user-friendly, without error-prone PCR, with a wide detection range and simple operating protocol without the requirement for sophisticated equipment. Graphical Abstract Schematic representation of the QD-encapsulated liposome-based strategy to amplify fluorescence signal for optical detection of telomerase activity.

Design and development of PCR-free highly sensitive electrochemical assay for detection of telomerase activity using Nano-based (liposomal) signal amplification platform.

Telomerase, which has been detected in almost all kinds of cancer tissues, is considered as an important tumor marker for early cancer diagnostics. In the present study, an electrochemical method based on liposomal signal amplification platform is proposed for simple, PCR-free, and highly sensitive detection of human telomerase activity, extracted from A549 cells. In this strategy, telomerase reaction products, which immobilized on streptavidin-coated microplate, hybridized with biotinylated capture probes. Then, dopamine-loaded biotinylated liposomes are attached through streptavidin to biotinylated capture probes. Finally, liposomes are ruptured by methanol and the released-dopamine is subsequently measured using differential pulse voltammetry technique by multi-walled carbon nanotubes modified glassy carbon electrode. Using this strategy, the telomerase activity extracted from 10 cultured cancer cells could be detected. Therefore, this approach affords high sensitivity for telomerase activity detection and it can be regarded as an alternative to telomeric repeat amplification protocol assay, having the advantages of simplicity and less assay time.

De novo likelihood-based measures for comparing genome assemblies.

BACKGROUND: The current revolution in genomics has been made possible by software tools called genome assemblers, which stitch together DNA fragments "read" by sequencing machines into complete or nearly complete genome sequences. Despite decades of research in this field and the development of dozens of genome assemblers, assessing and comparing the quality of assembled genome sequences still relies on the availability of independently determined standards, such as manually curated genome sequences, or independently produced mapping data. These "gold standards" can be expensive to produce and may only cover a small fraction of the genome, which limits their applicability to newly generated genome sequences. Here we introduce a de novo probabilistic measure of assembly quality which allows for an objective comparison of multiple assemblies generated from the same set of reads. We define the quality of a sequence produced by an assembler as the conditional probability of observing the sequenced reads from the assembled sequence. A key property of our metric is that the true genome sequence maximizes the score, unlike other commonly used metrics. RESULTS: We demonstrate that our de novo score can be computed quickly and accurately in a practical setting even for large datasets, by estimating the score from a relatively small sample of the reads. To demonstrate the benefits of our score, we measure the quality of the assemblies generated in the GAGE and Assemblathon 1 assembly "bake-offs" with our metric. Even without knowledge of the true reference sequence, our de novo metric closely matches the reference-based evaluation metrics used in the studies and outperforms other de novo metrics traditionally used to measure assembly quality (such as N50). Finally, we highlight the application of our score to optimize assembly parameters used in genome assemblers, which enables better assemblies to be produced, even without prior knowledge of the genome being assembled. CONCLUSION: Likelihood-based measures, such as ours proposed here, will become the new standard for de novo assembly evaluation.

DNACLUST: accurate and efficient clustering of phylogenetic marker genes.

BACKGROUND: Clustering is a fundamental operation in the analysis of biological sequence data. New DNA sequencing technologies have dramatically increased the rate at which we can generate data, resulting in datasets that cannot be efficiently analyzed by traditional clustering methods.This is particularly true in the context of taxonomic profiling of microbial communities through direct sequencing of phylogenetic markers (e.g. 16S rRNA) - the domain that motivated the work described in this paper. Many analysis approaches rely on an initial clustering step aimed at identifying sequences that belong to the same operational taxonomic unit (OTU). When defining OTUs (which have no universally accepted definition), scientists must balance a trade-off between computational efficiency and biological accuracy, as accurately estimating an environment's phylogenetic composition requires computationally-intensive analyses. We propose that efficient and mathematically well defined clustering methods can benefit existing taxonomic profiling approaches in two ways: (i) the resulting clusters can be substituted for OTUs in certain applications; and (ii) the clustering effectively reduces the size of the data-sets that need to be analyzed by complex phylogenetic pipelines (e.g., only one sequence per cluster needs to be provided to downstream analyses). RESULTS: To address the challenges outlined above, we developed DNACLUST, a fast clustering tool specifically designed for clustering highly-similar DNA sequences.Given a set of sequences and a sequence similarity threshold, DNACLUST creates clusters whose radius is guaranteed not to exceed the specified threshold. Underlying DNACLUST is a greedy clustering strategy that owes its performance to novel sequence alignment and k-mer based filtering algorithms.DNACLUST can also produce multiple sequence alignments for every cluster, allowing users to manually inspect clustering results, and enabling more detailed analyses of the clustered data. CONCLUSIONS: We compare DNACLUST to two popular clustering tools: CD-HIT and UCLUST. We show that DNACLUST is about an order of magnitude faster than CD-HIT and UCLUST (exact mode) and comparable in speed to UCLUST (approximate mode). The performance of DNACLUST improves as the similarity threshold is increased (tight clusters) making it well suited for rapidly removing duplicates and near-duplicates from a dataset, thereby reducing the size of the data being analyzed through more elaborate approaches.

Alignment and clustering of phylogenetic markers--implications for microbial diversity studies.

BACKGROUND: Molecular studies of microbial diversity have provided many insights into the bacterial communities inhabiting the human body and the environment. A common first step in such studies is a survey of conserved marker genes (primarily 16S rRNA) to characterize the taxonomic composition and diversity of these communities. To date, however, there exists significant variability in analysis methods employed in these studies. RESULTS: Here we provide a critical assessment of current analysis methodologies that cluster sequences into operational taxonomic units (OTUs) and demonstrate that small changes in algorithm parameters can lead to significantly varying results. Our analysis provides strong evidence that the species-level diversity estimates produced using common OTU methodologies are inflated due to overly stringent parameter choices. We further describe an example of how semi-supervised clustering can produce OTUs that are more robust to changes in algorithm parameters. CONCLUSIONS: Our results highlight the need for systematic and open evaluation of data analysis methodologies, especially as targeted 16S rRNA diversity studies are increasingly relying on high-throughput sequencing technologies. All data and results from our study are available through the JGI FAMeS website http://fames.jgi-psf.org/.

Inexact Local Alignment Search over Suffix Arrays.

We describe an algorithm for finding approximate seeds for DNA homology searches. In contrast to previous algorithms that use exact or spaced seeds, our approximate seeds may contain insertions and deletions. We present a generalized heuristic for finding such seeds efficiently and prove that the heuristic does not affect sensitivity. We show how to adapt this algorithm to work over the memory efficient suffix array with provably minimal overhead in running time.We demonstrate the effectiveness of our algorithm on two tasks: whole genome alignment of bacteria and alignment of the DNA sequences of 177 genes that are orthologous in human and mouse. We show our algorithm achieves better sensitivity and uses less memory than other commonly used local alignment tools.