Biology subjects

Albrecht, F.

Publications and source records attributed to Albrecht, F..

4 recordsLinked to original sources

bioRxiv2025

Scalable and interpretable secretion system annotation with Sismis

Secretion systems play critical roles in bacterial growth, survival, and pathogenesis. Genes encoding secretion system components often co-occur together as gene clusters in bacterial (meta)genomes. However, existing tools for secretion system annotation are unable to utilize genomic context to make predictions and are unable to detect secretion systems of novel architecture. Here, we present Sismis (secretion system discovery tool; https://github.com/lmc297/Sismis), a scalable, interpretable, machine learning-based tool, which detects and classifies single-locus secretion systems in bacterial (meta)genomes with high accuracy (test set area-under-the-curve [AUC] values of 0.71 and 0.92 for precision-recall [PR] and receiver operating characteristic [ROC] curves, respectively). When applied to {approx}700k prokaryotic (meta)genomes, Sismis identifies 747, 439 total secretion systems comprising 15, 612 major secretion system families, >80% of which contain no previously known/annotated secretion systems. To facilitate further exploration of these data, we present the Sismis Atlas (https://sismis.microbe.dev/), an interactive secretion system database, which we use to identify a largely uncharacterized cluster of secretion systems with tight adherence (Tad) pili-like characteristics. Altogether, Sismis and its companion atlas enable accurate and interpretable secretion system annotation, exploration, and discovery at an unprecedented scale. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/675188v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@89dec2org.highwire.dtl.DTLVardef@17fa652org.highwire.dtl.DTLVardef@18064b9org.highwire.dtl.DTLVardef@54deaa_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

Scalable single-cell metagenomic analysis with Bascet and Zorn

Single-cell metagenomic sequencing (scMetaG) can provide maximum-resolution insights into complex microbial communities. However, existing bioinformatic tools are not equipped to handle the massive amounts of data generated by novel high-throughput scMetaG methods. Here, we present a bioinformatic toolkit for complete, end-to-end scMetaG analysis: (i) Bascet, a command-line suite designed to scale to massive scMetaG datasets ([≥]1 million cells); (ii) Zorn, an R package/workflow manager that enables reproducible scMetaG data analysis, exploration, and visualization (http://zorn.henlab.org/). Enabled by recent advances in droplet microfluidics, we use Bascet and Zorn to develop and optimize a high-throughput scMetaG method on a ten-species mock community. To showcase their utility on a real-world sample, we use Bascet and Zorn to characterize a human saliva sample, generating single-amplified genomes (SAGs) from >10k prokaryotic cells. Overall, Bascet and Zorn enable reproducible scMetaG analysis, allowing users to query microbiomes at unprecedented resolution and scale.

microbiology↗

bioRxiv2024

Mapping the niche of breast cancer metastases in lung and liver

Breast cancer progression to visceral organs such as lung and liver is regarded as a dreadful event, unequivocally associated with a poor prognosis. Yet, these vital sites are characterized by highly diverse cellular microenvironments and physiological functions, suggesting that they may influence cancer cells behavior in divergent ways. Unexpectedly, we find that while the liver microenvironment fosters metastasis-promoting properties and boosts secondary spread, the lungs impose a roadblock to the same processes. Using patient data and tissues from rapid autopsy, as well as mouse models with barcode-mediated metastasis tracing, niche labeling technology and single cell analysis of both tumor cells and their direct microenvironment, we dissect cellular and molecular microenvironmental factors that impose this differential behavior. Among these, we identify BMP2-producing endothelial cells as critical players within the liver metastatic niche, capable to enhance metastasis-to-metastasis dissemination. Targeting BMP2 receptor on breast cancer cells suppresses their metastasis-forming ability. Altogether, we reveal a contrast in the site-specific behavior of lung and liver metastases in breast cancer, highlighting microenvironmental factors that contribute to this diversity, as well as organ-specific opportunities for intervention.

cancer biology↗

bioRxiv2022

ALiCE: A versatile, high yielding and scalable eukaryotic cell-free protein synthesis (CFPS) system

Eukaryotic cell-free protein synthesis (CFPS) systems have the potential to simplify and speed up the expression and high-throughput analysis of complex proteins with functionally relevant post-translational modifications (PTMs). However, low yields and the inability to scale such systems have so far prevented their widespread adoption in protein research and manufacturing. Here, we present a detailed demonstration for the capabilities of a CFPS system derived from Nicotiana tabacum BY-2 cell culture (BY-2 lysate; BYL). BYL is able to express diverse, functional proteins at high yields in under 48 hours, complete with native disulfide bonds and N-glycosylation. An optimised version of the technology is commercialised as ALiCE(R), engineered for high yields of up to 3 mg/mL. Recent advances in the scaling of BYL production methodologies have allowed scaling of the CFPS reaction. We show simple, linear scale-up of batch mode reporter proten expression from a 100 L microtiter plate format to 10 mL and 100 mL volumes in standard Erlenmeyer flasks, culminating in preliminary data from 1 L reactions in a CELL-tainer(R) CT20 rocking motion bioreactor. As such, these works represent the first published example of a eukaryotic CFPS reaction scaled past the 10 mL level by several orders of magnitude. We show the ability of BYL to produce the simple reporter protein eYFP and large, multimeric virus-like particles directly in the cytosolic fraction. Complex proteins are processed using the native microsomes of BYL and functional expression of multiple classes of complex, difficult-to-express proteins is demonstrated, specifically: a dimeric, glycoprotein enzyme, glucose oxidase; the monoclonal antibody adalimumab; the SARS-Cov-2 receptor-binding domain; human epidermal growth factor; and a G protein-coupled receptor membrane protein, cannabinoid receptor type 2. Functional binding and activity are shown using a combination of surface plasmon resonance techniques, a serology-based ELISA method and a G protein activation assay. Finally, in-depth post-translational modification (PTM) characterisation of purified proteins through disulfide bond and N-glycan analysis is also revealed - previously difficult in the eukaryotic CFPS space due to limitations in reaction volumes and yields. Taken together, BYL provides a real opportunity for screening of complex proteins at the microscale with subsequent amplification to manufacturing-ready levels using off-the-shelf protocols. This end-to-end platform suggests the potential to significantly reduce cost and the time-to-market for high value proteins and biologics.

biochemistry↗