Biology subjects

Majka, M.

Publications and source records attributed to Majka, M..

4 recordsLinked to original sources

bioRxiv2023

Inference of Genomic Landscapes using Ordered Hidden Markov Models with Emission Densities (oHMMed)

BackgroundGenomes are inherently inhomogeneous, with features such as base composition, recombination, gene density, and gene expression varying along chromosomes. Evolutionary, biological, and biomedical analyses aim to quantify this variation, account for it during inference procedures, and ultimately determine the causal processes behind it. Since sequential observations along chromosomes are not independent, it is unsurprising that autocorrelation patterns have been observed e.g., in human base composition. In this article, we develop a class of Hidden Markov Models (HMMs) called oHMMed (ordered HMM with emission densities, the corresponding R package of the same name is available on CRAN): They identify the number of comparably homogeneous regions within autocorrelated observed sequences. These are modelled as discrete hidden states; the observed data points are realisations of continuous probability distributions with state-specific means that enable ordering of these distributions. The observed sequence is labelled according to the hidden states, permitting only neighbouring states that are also neighbours within the ordering of their associated distributions. The parameters that characterise these state-specific distributions are inferred. ResultsWe apply our oHMMed algorithms to the proportion of G and C bases (modelled as a mixture of normal distributions) and the number of genes (modelled as a mixture of poisson-gamma distributions) in windows along the human, mouse, and fruit fly genomes. This results in a partitioning of the genomes into regions by statistically distinguishable averages of these features, and in a characterisation of their continuous patterns of variation. In regard to the genomic G and C proportion, this latter result distinguishes oHMMed from segmentation algorithms based in isochore or compositional domain theory. We further use oHMMed to conduct a detailed analysis of variation of chromatin accessibility (ATAC-seq) and epigenetic markers H3K27ac and H3K27me3 (modelled as a mixture of poisson-gamma distributions) along the human chromosome 1 and their correlations. ConclusionsOur algorithms provide a biologically assumption-free approach to characterising genomic landscapes shaped by continuous, autocorrelated patterns of variation. Despite this, the resulting genome segmentation enables extraction of compositionally distinct regions for further downstream analyses.

bioinformatics↗

bioRxiv2023

Synthetic neuromelanin as a trigger of inflammation in the brain, new mouse model of Parkinson's disease

Parkinsons disease (PD) is a neurodegenerative disease that is an increasing threat to an aging society. The idiopathic form of PD accounts for over 90% of all cases, and the current etiology is still unknown. One of the reasons hindering research on this form of PD is the lack of an appropriate animal models. Among mouse models of the disease, those based on the administration of neurotoxins such as 1-methyl-4-phenyl-1,2,3,6- tetrahydropyridine (MPTP) or 6-hydroxydopamine (6-OHDA) to the substantia nigra pars compacta (SNpc) or striatum are predominantly used. In these models, there are metabolic disturbances causing oxidative stress in the SNpc or striatum, which ultimately leads to the death of dopaminergic neurons. However, the models used so far have serious limitations, most of all they do not fully reflect the processes occurring in the course of the disease and do not consider the involvement of inflammation in the etiology and pathogenesis of PD. In this study we show that the administration of synthetic neuromelanin, which activates astrocytes and microglia, induces the inflammation and may be involved in degeneration of dopaminergic neurons. Neuromelanin under physiological conditions acts as a neuroprotector, however, released from dying dopaminergic neurons is an important factor activating astrocytes, microglia and causing neuroinflammation. Since one of the causes of Parkinsons appear to be the death of dopaminergic neurons overloaded with neuromelanin and consequent pathological activation of microglia, the use of synthetic neuromelanin reflect the natural pathological processes occurring during the development of the disease.

neuroscience↗

bioRxiv2023

Mitochondrial fitness influences neuronal excitability of dopaminergic neurons from patients with idiopathic form of Parkinson's disease

Parkinson disease is the second most common neurodegenerative disease defined by presence of Lewy bodies and the loss of dopaminergic neurons in the substantia nigra pars compacta (SNc). There are three types of PD - familial, early-onset and idiopathic. Idiopathic PD (IPD) accounts for approximately 90% of all PD cases. Mitochondrial dysfunction accompanies the pathogenesis of Parkinsons disease. Loss of mitochondrial function increases oxidative stress and calcium buffering, which in turn hinders the production of ATP and disrupts the functioning of dopaminergic neurons. The main barrier in PD research was the lack of proper human models to study the mechanisms of PD development and progression. Using induced pluripotent stem (iPS) cells we generated patient-specific dopaminergic neurons. We observed differences in the mitochondria fitness but not differences in mitochondria mass, morphology or membrane potential. Expression of OXPHOS mitochondrial complexes were lower in PD patients in comparison to control group what resulted in changes in mitochondria respiratory status. We observed also lower expression levels of Na+/K+-ATPase subunits and ATP-sensitive K+ (K-ATP) channel subunits. The lower oxygen consumption rate and extracellular acidification rate values were observed in dopaminergic progenitors and iPSC from PD patients compared to the control group. Importantly, observed decrease in the availability of ATP and in the energy consumption, as well as changes in acidification, may constitute contributing factors to the observed reduced neuronal excitability of PD patients dopaminergic neurons.

neuroscience↗

bioRxiv2022

Impact of AMPK on cervical carcinoma progression and metastasis

Cervical cancer (CC) is the fourth most common malignant neoplasm among women. Late diagnosis is directly associated with the incidence of metastatic disease and remarkably limits the effectiveness of conventional anticancer therapies at the advanced tumor stage. In this study, we investigated the role of 5AMP-activated kinase (AMPK) in the metastatic progression of cervical cancer. Since the epithelial mesenchymal transition (EMT) is known as major mechanism enabling cancer cell metastasis, cell lines, which accurately represent this process, have been used as a research model. We used C-4I and HTB-35 cervical cancer cell lines representing distant stages of the disease, in which we genetically modified the expression of the AMPK catalytic subunit . We have shown that tumor progression leads to metabolic deregulation which results in reduced expression and activity of AMPK. We also demonstrated that AMPK is related to the ability of cells to acquire invasive phenotype and potential for in vivo metastases, and its activity may inhibit these processes. Our findings support the hypothesis that AMPK is a promising therapeutic target and modulation of its expression and activity may improve the efficacy of cervical cancer treatment.

cancer biology↗