Biology subjects

Wegrzyn, M.

Publications and source records attributed to Wegrzyn, M..

5 recordsLinked to original sources

bioRxiv2025

Characterisation of novel bacteriophages against the cattle pathogen Moraxella bovis

BackgroundInfectious bovine keratoconjunctivitis is the most important cattle ocular disease worldwide. The infection is primarily caused by Moraxella bovis and is a highly contagious disease that significantly affects cattle welfare. Currently, antibiotic medication is the primary treatment for infectious bovine keratoconjunctivitis. However, with rising concerns over antibiotic resistance, we propose developing a more targeted therapeutic strategy using bacteriophages (phages). Materials and MethodsWe have isolated the first known Moraxella bovis phages, characterised them according to their genome sequence, local virulence index and with transmission electron microscopy. The host ranges were assessed using 41 clinical M. bovis strains isolated from infected cows. ResultsFour phages were isolated and characterised. Comparative analysis identified a high degree of genomic similarity between the phages MB15, MB16, MB26 and MB43. MB43 was the most distinct, with the smallest host range phenotype. ConclusionsThe isolated phages show therapeutic potential for further development against Moraxella infections.

microbiology↗

bioRxiv2019

Volume-wise analysis of fMRI time series allows accurate prediction of language lateralization

Using fMRI as a clinical tool, for example for lateralizing language, requires that it provides accurate results on the individual level. However, using a single voxel-wise activity map per patient limits how well the uncertainty associated with a decision can be estimated. Here, we explored how using a "volume-wise" analysis, where the lateralization of each time point of a patients fMRI session is evaluated independently, could support clinical decision making. Ninety-six patients with epilepsy who performed a language fMRI were analyzed retrospectively. Results from Wada testing were used as an indication of true language lateralization. Each patients 200 fMRI volumes were correlated with an independent template of prototypical lateralization. Depending on the strength of correlation with the template, each volume was classified as indicating either left-lateralized, bilateral or right-lateralized language. A decision about the patients language lateralization was then made based on how most volumes were classified. The results show that, using a simple majority vote, accuracies of 84% were reached in a sample of 63 patients with high-quality data. When 33 patients with datasets previously deemed inconclusive were added, the same accuracy was reached when more than 43% of a patients volumes were in agreement with each other. Increasing this cutoff to 51% volumes with agreeing classifications allowed for excluding all inconclusive cases and reaching accuracies over 90% for the remaining cases. Further increasing the cutoff to 65% agreeing volumes resulted in correct predictions for all remaining patients. The study confirms the usefulness of fMRI for language lateralization in patients with epilepsy, by demonstrating high accuracies. Furthermore, it illustrates how the diagnostic yield of individual volumes of fMRI data can be increased using simple similarity measures. The accuracy of our approach increased with the number of agreeing volumes, and thus allowed estimating the uncertainty associated with each individual diagnosis.

neuroscience↗

bioRxiv2019

Protein kinase B controls Mycobacterium tuberculosis growth via phosphorylation of the global transcriptional regulator Lsr2

Mycobacterium tuberculosis is able to persist in the body through months of multi-drug therapy. Mycobacteria possess a wide range of regulatory proteins, including the essential protein kinase B (PknB), that control transitions between growth states. Here, we establish that depletion of PknB in replicating M. tuberculosis results in transcriptional adaptations that implicate the DNA-binding protein Lsr2 in coordinating these changes. We show that Lsr2 is phosphorylated by PknB, and that phosphorylation of Lsr2 at threonine 112 is important for M. tuberculosis growth and survival under hypoxic conditions. Fluorescence anisotropy and electrophoretic mobility shift assays demonstrate that phosphorylation reduces Lsr2 binding to DNA, and ChIP-sequencing confirms increased DNA binding of a phosphoablative (T112A) Lsr2 mutant in M. tuberculosis. Altered expression of target genes in T112A Lsr2 compared to wild type Lsr2 M. tuberculosis offers further evidence that phosphorylation mediates expression of the Lsr2 regulon. Structural studies reveal increased dynamics of the Lsr2 DNA binding domain from a T112D phosphomimetic Lsr2 mutant, providing a molecular basis for decreased DNA binding by phosphorylated Lsr2. Our findings suggest that, the essential protein kinase, PknB controls M. tuberculosis growth and adaptations to the changing host environment by phosphorylating the global transcriptional regulator Lsr2.

microbiology↗

bioRxiv2019

Quantifying the Confidence in fMRI-based Language Lateralisation through Laterality Index Deconstruction

In epilepsy patients, language lateralisation is an important part of the presurgical diagnostic process. Using task-based fMRI, language lateralisation can be determined by visual inspection of activity patterns or by quantifying the difference in left- and right-hemisphere activity using variations of a basic formula [(L-R)/(L+R)]. However, the values of this laterality index (LI) depend on the choice of activity thresholds and regions of interest. The diagnostic utility of the LI also depends on how its continuous values are translated into categorical decisions about a patients language lateralisation. Here, we analysed fMRI data from 712 epilepsy patients who performed a verbal fluency task. Each fMRI data set was evaluated by a trained human rater as depicting left-sided, right-sided, or bilateral lateralisation or as being inconclusive. We used data-driven methods to define the activity thresholds and regions of interest used for LI computation and to define a classification scheme that allowed us to translate the LI values into categorical decisions. By deconstructing the LI into measures of laterality (L-R) and strength (L+R), we also modelled the relationship between activation strength and conclusiveness of a data set. In a held-out data set, predictions reached 91% correct when using only conclusive data and 82% when inconclusive data were included. Although only trained on human evaluations of fMRIs, the approach generalised to the prediction of language Wada test results, allowing for significant above-chance accuracies. Compared against different existing methods of LI-computation, our approach improved the identification of inconclusive cases and increased the accuracy with which decisions for the remaining data could be made. We discuss how this approach can support clinicians in assessing fMRI data on a single-case level, deciding whether lateralisation can be determined with sufficient certainty or whether additional information is needed.

neuroscience↗

bioRxiv2018

Thought experiment: Decoding cognitive processes from the fMRI data of one individual

Cognitive processes, such as the generation of language, can be mapped onto the brain using fMRI. These maps can in turn be used for decoding the respective processes from the brain activation patterns. Given individual variations in brain anatomy and organization, analyzes on the level of the single person are important to improve our understanding of how cognitive processes correspond to patterns of brain activity. They also allow to advance clinical applications of fMRI, because in the clinical setting making diagnoses for single cases is imperative. In the present study, we used mental imagery tasks to investigate language production, motor functions, visuo-spatial memory, face processing, and resting-state activity in a single person. Analysis methods were based on similarity metrics, including correlations between training and test data, as well as correlations with maps from the NeuroSynth meta-analysis. The goal was to make accurate predictions regarding the cognitive domain (e.g. language) and the specific content (e.g. animal names) of single 30-second blocks. Four teams used the dataset, each blinded regarding the true labels of the test data. Results showed that the similarity metrics allowed to reach the highest degrees of accuracy when predicting the cognitive domain of a block. Overall, 23 of the 25 test blocks could be correctly predicted by three of the four teams. Excluding the unspecific rest condition, up to 10 out of 20 blocks could be successfully decoded regarding their specific content. The study shows how the information contained in a single fMRI session and in each of its single blocks can allow to draw inferences about the cognitive processes an individual engaged in. Simple methods like correlations between blocks of fMRI data can serve as highly reliable approaches for cognitive decoding. We discuss the implications of our results in the context of clinical fMRI applications, with a focus on how decoding can support functional localization.

neuroscience↗