Biology subjects

Kovacs, K.

Publications and source records attributed to Kovacs, K..

5 recordsLinked to original sources

bioRxiv2022

Engineering Nanowires in Bacteria to Elucidate Electron Transport Structural Functional Relationships

Bacterial pilin nanowires are protein complexes, suggested to possess electroactive capabilities forming part of the cells bioenergetic programming. Their role is thought to be linked to facilitating electron transfer with the external environment to permit metabolism and cell-to-cell communication. There is a significant debate, with varying hypotheses as to the nature of the proteins currently lying between type-IV pilin-based nanowires and polymerised cytochrome-based filaments. Importantly, to date, there is a very limited structure-function analysis of these structures within whole bacteria. In this work, we engineered Cupriavidus necator H16, a model autotrophic organism to express differing aromatic modifications of type-IV pilus proteins to establish structure-function relationships on conductivity and the effects this has on pili structure. This was achieved via a combination of high-resolution PeakForce tunnelling atomic force microscopy (PeakForce TUNA) technology, alongside conventional electrochemical approaches enabling the elucidation of conductive nanowires emanating from whole bacterial cells for the first time. This work is the first example of functional type-IV pili protein nanowires produced under aerobic conditions using a CN chassis. This work has far-reaching consequences in understanding the basis of bio-electrical communication between cells and with their external environment. O_FIG O_LINKSMALLFIG WIDTH=182 HEIGHT=200 SRC="FIGDIR/small/510814v2_ufig1.gif" ALT="Figure 1"> View larger version (90K): org.highwire.dtl.DTLVardef@134d026org.highwire.dtl.DTLVardef@4d84f3org.highwire.dtl.DTLVardef@15379fcorg.highwire.dtl.DTLVardef@16d942c_HPS_FORMAT_FIGEXP M_FIG C_FIG Graphical abstract displaying theoretical PilA monomer models (left), PeakForce TUNA atomic force microscopy contact current images (right) of wild-type (top) and modified with increased tyrosine content (bottom) PilA filaments expressed by Cupriavidus necator H16 cells.

bioengineering↗

bioRxiv2021

Selective effects of biological and chronological age on the development of cognitive abilities in adolescence

Adolescent human development is not only shaped by the mere passing of time and accumulating experience, but it also depends on pubertal timing and the cascade of maturational processes orchestrated by gonadal hormones. Although individual variability in puberty onset confounds adolescent studies, it has not been efficiently controlled for. Here we introduce ultrasonic bone age assessment to estimate biological maturity and disentangle the independent effects of chronological and biological age on adolescent cognitive abilities. Comparing cognitive performance of participants with different skeletal maturity we uncover the striking impact of biological age on both IQ and specific abilities. We find that biological age has a selective effect on abilities: more mature individuals within the same age group have higher working memory capacity and processing speed, while those with higher chronological age have better verbal abilities, independently of their maturity. Bone age appears to be a surprisingly strong predictor of cognitive abilities, and it seems that a teens IQ is determined by biological age.

neuroscience↗

bioRxiv2019

Efficient treatment of a preclinical inflammatory bowel disease model with engineered bacteria

We developed an engineered bacterium based, RNA interference mediated therapeutic method to significantly reduce the symptoms in the most frequently used animal model of inflammatory bowel disease. This transkingdom RNA interference strategy was based on the non-pathogenic E. coli MDS42 strain, which was engineered to constitutively produce invasin and histeriolysin cytolysin. These proteins enabled the bacteria first to invade the colon epithelium and then degrade in the phagosome. This allowed the delivery of a plasmid encoding shRNA targeting TNF alpha into the cytoplasm of the target cells. The expression levels of TNF alpha and other cytokines significantly decreased and the inflammatory symptoms were significantly reduced. With further safety modifications this method could serve as a safe and side-effect free alternative to biologicals targeting TNF-alpha.

synthetic biology↗

bioRxiv2019

Unmatched level of molecular convergence among deeply divergent complex multicellular fungi

Convergent evolution is pervasive in nature, but it is poorly understood how various constraints and natural selection limit the diversity of evolvable phenotypes. Here, we report that, despite >650 million years of divergence, the same genes have repeatedly been co-opted for the development of complex multicellularity in the two largest clades of fungi--the Ascomycota and Basidiomycota. Co-opted genes have undergone duplications in both clades, resulting in >81% convergence across shared multicellularity-related families. This convergence is coupled with a rich repertoire of multicellularity-related genes in ancestors that predate complex multicellular fungi, suggesting that the coding capacity of early fungal genomes was well suited for the repeated evolution of complex multicellularity. Our work suggests that evolution may be predictable not only when organisms are closely related or are under similar selection pressures, but also if the genome biases the potential evolutionary trajectories organisms can take, even across large phylogenetic distances.

evolutionary biology↗

bioRxiv2018

Locoregional Radiogenomic Models Capture Gene Expression Heterogeneity in Glioblastoma

Radiogenomics mapping noninvasively determines important relationships between the molecular genotype and imaging phenotype of various tumors, allowing advances in both clinical care and cancer research. While early work has shown its technical feasibility, here we extend radiogenomic mapping to a locoregional level that can account for the molecular heterogeneity of tumors. To achieve this, our data processing pipeline relies on three main steps: 1) the use of multi-omics data fusion to generate a set of 100 interpretable gene modules, 2) the use of patch-based image analysis (specifically of contrast-enhanced T1-weighted weighted MR images) combined with Generalized Linear Models (GLM) to establish potential links between module expressions and local MR signal, and 3) the use of expression heatmaps based on GLMs decision values to explore visualization of tumor molecular heterogeneity. The performance of the proposed approach was evaluated using a leave-one-patient-out crossvalidation method as well as a separate validation data set. The top performing models were based on a small set of 20 features and yielded Area Under the receiver operating characteristic Curve (AUC) above 0.65 on the validation cohort for eight modules. Next, we demonstrate the clinical and biological interpretation of four modules using molecular expression heatmaps superimposed on clinical radiographic images, showing the potential for assessing tumor molecular heterogeneity and the utility of this method for precision treatment in clinical decision making and imaging surveillance.

bioinformatics↗