Molecular Mechanisms of Oncogenesis through the Lens of Nucleosomes and Histones
At the cellular level, cancer is the disease of both the
genome and the epigenome, and the interplay between genetic
mutations and epigenetic states may occur at the level of
elementary chromatin units, the nucleosomes. They are formed
by a segment of DNA wrapped around an octamer of histone
proteins. In this review, we survey various mechanisms of cancer
etiology and progression mediated by histones and nucleosomes.
In particular, we discuss the effects of mutations in histones,
changes in their expression and slicing on epigenetic dysregulation
and carcinogenesis. The links between cancer phenotypes and
differential expression of histone variants and isoforms are
summarized. Finally, we discourse the geometric and steric effects
of DNA compaction in nucleosomes on DNA mutation rate,
interactions with transcription factors, including pioneer transcription factors, and prospects of cancer cells’ genome and epigenome editing.
Liquid chromatography-tandem mass spectrometry was used to analyze plasma proteins of volunteers (control) and patients with glioblastoma multiform (GBM). A database search was pre-set with a variable post-translational modification (PTM): phosphorylation, acetylation or ubiquitination. There were no significant differences between the control and the GBM groups regarding the number of protein identifications, sequence coverage or number of PTMs. However, in GBM plasma, we unambiguously observed a decreased fraction in post-translationally modified peptides identified with high quality. The disease-specific PTM patterns were extracted and mapped to the set of FDA-approved plasma protein markers. Decreases of 46% and 24% in the number of acetylated and ubiquitinated peptides, respectively, were observed in the GBM samples. Significance of capturing disease-associated patterns of protein modifications was envisaged.
With the advances in the sequencing technology the International Cancer Genome Consortium (ICGC)  and The Cancer Genome Atlas (TCGA)  collected data on more than 16 000 genome-wide pairs tumor-normal tissue providing a valuable resource to study cancer mutations. In this research we focus on pre- evaluation of the relationship between cancer breakpoint hotspots and DNA regions potentially forming secondary structures such as stem-loops (cruciforms) and quadru- plexes. We performed analysis of 2 234 samples covering 10 cancer types and built machine-learning models predicting cancer breakpoint distribution over chromosome based on the density distribution of stem-loops and quadruplexes. We developed pro- cedure for machine learning models building and evaluation as the considered data are extremely imbalanced and it is needed to get reliable estimate of prediction power. We conducted a set of experiments to select the best appropriate resampling scheme, class balancing technique and parameters of machine learning algorithms. The best final models were applied to cancer breakpoints data. From the performed analysis it could be concluded that the relationship between cancer breakpoints hotspots and studied DNA secondary structures exists, however, generally, this relationship is weak for stem-loops, but higher for quadruplexes. We also found differences in model predictive power depending on cancer types. Thus, stem-loop-based model performs better for pancreatic, prostate, ovary, uterus, brain and liver cancer, and quadruplex- based model works better for blood, bone, skin and breast cancer.
One of the key advances in genome assembly that has led to a significant improvement in contig lengths has been improved algorithms for utilization of paired reads (mate-pairs). While in most assemblers, mate-pair information is used in a post-processing step, the recently proposed Paired de Bruijn Graph (PDBG) approach incorporates the mate-pair information directly in the assembly graph structure. However, the PDBG approach faces difficulties when the variation in the insert sizes is high. To address this problem, we first transform mate-pairs into edge-pair histograms that allow one to better estimate the distance between edges in the assembly graph that represent regions linked by multiple mate-pairs. Further, we combine the ideas of mate-pair transformation and PDBGs to construct new data structures for genome assembly: pathsets and pathset graphs.
Papers about natural protection territories
Many environmental stimuli present a quasi-rhythmic structure at different timescales that the brain needs to decompose and integrate. Cortical oscillations have been proposed as instruments of sensory de-multiplexing, i.e., the parallel processing of different frequency streams in sensory signals. Yet their causal role in such a process has never been demonstrated. Here, we used a neural microcircuit model to address whether coupled theta–gamma oscillations, as observed in human auditory cortex, could underpin the multiscale sensory analysis of speech. We show that, in continuous speech, theta oscillations can flexibly track the syllabic rhythm and temporally organize the phoneme-level response of gamma neurons into a code that enables syllable identification. The tracking of slow speech fluctuations by theta oscillations, and its coupling to gamma-spiking activity both appeared as critical features for accurate speech encoding. These results demonstrate that cortical oscillations can be a key instrument of speech de-multiplexing, parsing, and encoding.
Neuronal nicotinic acetylcholine receptors (NNRs) of the α7 subtype have been shown to contribute to the release of dopamine in the nucleus accumbens. The site of action and the underlying mechanism, however, are unclear. Here we applied a circuit modeling approach, supported by electrochemical in vivo recordings, to clarify this issue. Modeling revealed two potential mechanisms for the drop in accumbal dopamine efflux evoked by the selective α7 partial agonist TC-7020. TC-7020 could desensitize α7 NNRs located predominantly on dopamine neurons or glutamatergic afferents to them or, alternatively, activate α7 NNRs located on the glutamatergic afferents to GABAergic interneurons in the ventral tegmental area. Only the model based on desensitization, however, was able to explain the neutralizing effect of coapplied PNU-120596, a positive allosteric modulator. According to our results, the most likely sites of action are the preterminal α7 NNRs controlling glutamate release from cortical afferents to the nucleus accumbens. These findings offer a rationale for the further investigation of α7 NNR agonists as therapy for diseases associated with enhanced mesolimbic dopaminergic tone, such as schizophrenia and addiction