Biology subjects

Goncharov, A.

Publications and source records attributed to Goncharov, A..

6 recordsLinked to original sources

bioRxiv2026

Lab-on-a-3D-Printer for Democratized Reconfigurable Digital Microfluidics

Automation in the life sciences remains dominated by expensive, centralized robotic systems, leaving most laboratories unable to access precision robotic liquid handling. Here we present the Lab-on-a-3D-Printer (Lo3DP), a reconfigurable robotic microfluidic platform that repurposes the motion control, thermal regulation, and open-source programmability of consumer 3D printers to deliver laboratory-grade automation at a hardware cost below $500. By replacing the extruder with a multifunctional magnetic toolhead, Lo3DP actuates ferrofluid droplets with sub-100 {micro}m positioning accuracy and programmable volume control spanning 0.5-25 {micro}L, enabling the full repertoire of digital microfluidic operations within inexpensive laser-cut chips (<$3). We quantitatively validate system performance through long-term droplet transport exceeding 40,000 s without degradation, automated serial dilutions with high linearity (R{superscript 2} [≥] 0.99), and fully automated colorimetric nucleic acid amplification assays whose results match conventional benchtop workflows under tightly regulated isothermal conditions (CV {approx} 0.3%). By harnessing the global economies of scale of consumer 3D printers, Lo3DP provides accurate, reproducible, and programmable assay automation at a fraction of the cost and footprint of conventional systems, establishing a practical path toward desktop-scale, democratized laboratory robotics.

bioengineering↗

bioRxiv2024

Continuous Monitoring of Glucose and Oxygen using an Insertable Biomaterial-based Multianalyte Barcode Sensor

Chronic diseases including diabetes, cardiovascular diseases, and microvascular complications contribute significantly to global morbidity and mortality. Multiplexing technologies offer a promising approach for the simultaneous detection and management of comorbidities, providing comprehensive disease insights. In this work, we describe a miniaturized optical "barcode" sensor with high biocompatibility for continuous monitoring of glucose and oxygen. This enzymatic sensor relies on oxygen consumption in proportion to local glucose levels and the phosphorescence reporting of tissue oxygen with a lifetime-based probe. The sensor was designed to operate in a tissue environment with low levels of dissolved oxygen. The barcode sensor consists of a poly(ethylene) glycol diacrylate (PEGDA) hydrogel with four discrete compartments separately filled with glucose or oxygen-sensing phosphorescent microparticles. We evaluated the response of the barcode hydrogels to fluctuating glucose levels over the physiological range under low oxygen conditions, demonstrating controlled tuning of dynamic range and sensitivity. Moreover, the barcode sensor exhibited remarkable storage stability over 12 weeks, along with full reversibility and excellent reproducibility ([~]6% variability in phosphorescence lifetime). Electron beam sterilization had a negligible impact on the glucose response of the barcode sensors. Furthermore, our investigation revealed minimal phosphorescence lifetime changes in oxygen compartments while exhibiting increased lifetime in glucose-responsive compartments when subjected to alternating glucose concentrations (0 and 200 mg/dL), showcasing the sensors multianalyte sensing capabilities without crosstalk between compartments. Additionally, evaluation of tissue response to sensors inserted in pigs revealed appropriate biocompatibility of the barcodes.

bioengineering↗

bioRxiv2023

Single-tier point-of-care serodiagnosis of Lyme disease

Point-of-care (POC) serological testing provides actionable information for several difficult to diagnose illnesses, empowering distributed health systems. Accessible and adaptable diagnostic platforms that can assay the repertoire of antibodies formed against pathogens are essential to drive early detection and improve patient outcomes. Here, we report a POC serologic test for Lyme disease (LD), leveraging synthetic peptides tuned to be highly specific to the LD antibody repertoire across patients and compatible with a paper-based platform for rapid, reliable, and cost-effective diagnosis. A subset of antigenic epitopes conserved across Borrelia burgdorferi genospecies and targeted by IgG and IgM antibodies, were selected based on their seroreactivity to develop a multiplexed panel for a single-step measurement of combined IgM and IgG antibodies from LD patient sera. Multiple peptide epitopes, when combined synergistically using a machine learning-based diagnostic model, yielded a high sensitivity without any loss in specificity. We blindly tested the platform with samples from the U.S. Centers for Disease Control & Prevention (CDC) LD repository and achieved a sensitivity and specificity matching the lab-based two-tier results with a single POC test, correctly discriminating cross-reactive look-alike diseases. This computational LD diagnostic test can potentially replace the cumbersome two-tier testing paradigm, improving diagnosis and enabling earlier effective treatment of LD patients while also facilitating immune monitoring and surveillance of the disease in the community.

bioengineering↗

bioRxiv2022

Buffering role of HSP shapes the molecular evolution of mammalian and human genomes at short and long-term scales

Heat shock proteins in parallel with their main and originally discovered function - maintenance of folded proteins under stressful conditions, can play also background buffering role - by folding proteins with an excess of slightly-deleterious nonsynonymous variants (SDNV). Here we tested several scenarios of this buffering role. On the comparative species scale, we demonstrated that low-Ne species are characterized by a higher expression level of hsp90 which can be explained by the excess of SDNV. On the comparative tissue level, we showed that long-lived tissues have also a higher hsp90 expression level, which can be advantageous to maintain the functionality of proteins. On the comparative gene level, we demonstrated that purifying selection of hsp90 in low-Ne-species did not relax as strongly as it happens for control genes, similar to hsp90. Additionally, we demonstrated that hsp clients versus non-clients are characterised by decreased level of selective constraints; demonstrate stronger relaxation of purifying selection in low-Ne species; have an excess of slightly-deleterious variants associated with complex disease phenotypes in humans; have an excess of pathological variants associated with clinical phenotypes in humans, suggesting that clients, being buffered by hsp90 can degenerate a bit more as compared to non-clients. Altogether, our results show that the secondary role of hsp, buffering of SDNV, is widespread and universal affecting properties of species, tissues and genes. A deep understanding of the buffering role of hsp90 will help to predict the deleterious effect of each variant in the human genome more precisely as well as will extend the application of the effectively-neutral theory of molecular evolution.

evolutionary biology↗

bioRxiv2021

High prevalence and diversity of beta-lactamase-encoding bacteria in cryosoils and ancient permafrost

BackgroundAntimicrobial resistance is one of the major challenges affecting public health. It is mostly due to the continuous emergence of extended-spectrum {beta}-lactamase from various environments followed by their rapid dissemination and selection in clinical settings. The warming of Earths climate is the other global threat facing human society, in particular with the Arctic regions experiencing a twice faster warming than the global average and permafrost affected by widespread thawing. A potentially dreadful combination of these two threats would be the release and dispersion of harmful microbes that have remained confined to largely uninhabited Arctic regions, or are stored dormant in permafrost. MethodsEnvironmental DNA was isolated from 12 soil samples from various Arctic and subarctic pristine regions in Siberia (Yakutia and Kamchatka), including nine permafrost samples collected at various depths. The large datasets obtained from high throughput sequencing was assembled in contigs and their protein-gene contents predicted. We used exhaustive similarity searches to perform taxonomical assignments of bacterial, archaeal, and eukaryotic organisms, as well as DNA viruses. In addition, we specifically identified {beta}-lactamase genes and their prevalence per bacterial genome estimated through the detection of two universal single copy genes. FindingsA total of 9.217 1011 bp were exploited, leading to a total of 525,313 contigs at least 5kb in size. The DNA content of the various samples was found to be highly variable, not strictly correlated with the depth or radio-carbon-based deposit age, and most likely linked to the global density of microbes trapped in the corresponding permafrost layers. Bacteria account for more than 90% of the contigs in most samples, followed by Eukaryotes and Archaea (always lower than 10%). Viruses represented less than 2% of all contigs in all samples. The taxonomic profiles of surface cryosoils and deep permafrost samples exhibited a high diversity, including between permafrost samples originating from various depths in the same borehole. In all samples, bacterial contigs carrying different {beta}-lactamases from class A to D were identified. InterpretationNo clear common taxonomic feature could be found shared by surface cryosoils or ancient permafrost layers. However, most samples (9/12) exhibited a high frequency of {beta}-lactamase genes, with an estimated average close to 1 copy/bacterial genome. In addition to the well-documented reactivation of infectious ancient pathogens (bacteria, viruses, protozoa), we show now that global warming could contribute to the emergence of new antibiotic resistances through the mobilization by contemporary bacteria of ancient DNA released from thawing permafrost. FundingCNRS PRC research grant (PRC1484-2018) to C.A. E C-F was supported by a PhD grant (DGA/DS/MRIS) #2017 60 0004. GG and JS were funded by ERC PETA-CARB (#338335) and the HGF Impulse and Networking Fund (ERC-0013).

microbiology↗

bioRxiv2019

DEEP LEARNING-ENABLED POINT-OF-CARE SENSING USING MULTIPLEXED PAPER-BASED SENSORS

We present a deep learning-based framework to design and quantify point-of-care sensors. As its proof-of-concept and use-case, we demonstrated a low-cost and rapid paper-based vertical flow assay (VFA) for high sensitivity C-Reactive Protein (hsCRP) testing, a common medical test used for quantifying the degree of inflammation in patients at risk of cardio-vascular disease (CVD). A machine learning-based sensor design framework was developed for two key tasks: (1) to determine an optimal configuration of immunoreaction spots and conditions, spatially-multiplexed on a paper-based sensing membrane, and (2) to accurately infer the target analyte concentration based on the signals of the optimal VFA configuration. Using a custom-designed mobile-phone based VFA reader, a clinical study was performed with 85 human serum samples to characterize the quantification accuracy around the clinically defined cutoffs for CVD risk stratification. Results from blindly-tested VFAs indicate a competitive coefficient of variation of 11.2% with a linearity of R2 = 0.95; in addition to the success in the high-sensitivity CRP range (i.e., 0-10 mg/L), our results further demonstrate a mitigation of the hook-effect at higher CRP concentrations due to the incorporation of antigen capture spots within the multiplexed sensing membrane of the VFA. This paper-based computational VFA that is powered by deep learning could expand access to CVD health screening, and the presented machine learning-enabled sensing framework can be broadly used to design cost-effective and mobile sensors for various point-of-care diagnostics applications.

bioengineering↗