Biology subjects

Franklin, E.

Publications and source records attributed to Franklin, E..

8 recordsLinked to original sources

bioRxiv2026

Rapid reconstitution and kinase-controlled regulation of algal pyrenoid condensates in engineered Nicotiana benthamiana

The pyrenoid is an organelle found in nearly all algae that concentrates CO2 around Rubisco to enhance photosynthetic carbon fixation. Engineering a functional pyrenoid into C plants is a promising route to improve plant photosynthetic performance and yields. However, progress has been limited by the lack of a plant platform for rapidly testing candidate components. Here, we engineered N. benthamiana to make its chloroplast Rubisco holoenzyme compatible with C. reinhardtii pyrenoid proteins. Disruption of native N. benthamiana RBCS genes and complementation with the C. reinhardtii RBCS2 generated a Rubisco-recombinant background where transient expression of the Rubisco linker protein EPYC1 was sufficient to drive the formation of Rubisco-EPYC1 condensates. Co-expression with the algal pyrenoid kinase KEY1 shifted the multi-condensate state toward a single condensate per chloroplast by altering EPYC1 phosphorylation in planta, recapitulating C. reinhardtii pyrenoid regulation. Together, these results establish engineered N. benthamiana as a tractable platform for rapidly characterizing candidate pyrenoid proteins and provide a step toward reconstructing pyrenoid architecture and regulation in plants.

plant biology↗

bioRxiv2026

A bifunctional coiled-coil protein generates the membrane-within-condensate architecture of the CO2-fixing pyrenoid

How membranes are integrated into biomolecular condensates is a fundamental question in cell biology. In the algal pyrenoid, an organelle responsible for one-third of global carbon fixation, CO2-delivering thylakoid membranes must penetrate a phase-separated condensate of the CO2-fixing enzyme Rubisco, but the mechanism governing membrane recruitment into the condensate remains unknown. Here, we demonstrate that the Chlamydomonas reinhardtii protein MITH1 acts as a molecular anchor that brings membrane into the pyrenoid condensate. MITH1 dimerizes into an extended coiled coil with an N-terminal amphipathic helix that binds thylakoid membrane. The coiled coil contains multiple novel binding sites for the Rubisco large subunit, allowing the condensate to wet onto the membrane. The coiled coil extends away from the membrane and promotes membrane organization within the condensate. These findings solve a longstanding mechanistic question in pyrenoid biogenesis and reveal general principles for how membranes are integrated into biological condensates.

molecular biology↗

bioRxiv2025

Single-cell analysis of brain-derived Toxoplasma bradyzoites reveals a novel cell cycle regulated by AP2XI-6.

Toxoplasma gondii prevalence is due, in part, to its ability to persist in hosts while retaining the capacity to transmit and recrudesce. A process that is poorly understood. Through single-cell RNA profiling of in vivo-derived bradyzoites, we discovered that they are heterogeneous and not G1-arrested, as expected from in vitro studies. Instead, they progress through two cell cycles that branch from a single G1. While in G1b, in vivo-derived bradyzoites express cyst wall proteins predicted to replenish the wall that shields cysts. One cell cycle is common amongst tachyzoites and in vitro- and in vivo-derived bradyzoites; the other is unique to in vivo-derived bradyzoites (BCC). We demonstrated that AP2XI-6, expressed in G1 in vivo, is dispensable for tachyzoite growth and cyst formation in vitro but necessary for encystation in vivo. We propose that AP2XI-6 is a driver of replication through the BCC that is required for cyst maturation and persistence.

microbiology↗

bioRxiv2025

Effects of dibutyl phthalate (DBP) on life history traits and population dynamics of Daphnia magna: comparison of two exposure regimes

AbstractPhthalates are chemical products used as additives in the synthesis of plastics to increase their flexibility and resistance. Among the most frequently detected phthalates in the environment is dibutyl phthalate (DBP). Although ubiquitous in freshwater environments at concentrations in the ng/L to {micro}g/L range, studies on the effects of DBP on Daphnia magna have overlooked the potential effects of exposure at low concentrations ({micro}g/L order) and without solvent. Our work focuses on the chronic effects of DBP on life history traits (survival, growth, reproduction) in the freshwater model species, D. magna (Crustacea). Organisms were exposed to two exposure regimes: from the beginning of embryonic development or from the adult stage, at the third brood, when most of the energy investment in growth is complete. The results obtained show that the DBP exposure regime is an essential parameter in the effects on D. magna life history traits. While no significant response was observed in organisms exposed at the adult stage, disturbances to survival, growth and reproduction were observed at concentrations as low as the {micro}g/L range in organisms exposed at the beginning of embryonic development. The results also demonstrated that exposure to a concentration gradient of DBP results in different dose-dependent response typologies, depending on the life history traits measured. For survival, the dose-response relationship was non-monotonic, with greater juvenile mortality at intermediate concentrations (100, 280 and 500 {micro}g/L) than at higher concentrations (1000 and 2000 {micro}g/L). For effects on growth and reproduction, the responses followed classic monotonic dose-response relationships with low sensitivities. At the end of the experiment, the EC10-25d values were 1.01 {micro}g/L for reproduction and 79.22 {micro}g/L for growth. However, when calculated at earlier timepoints, the EC10-4d and the EC10-7d for growth were 0.25 {micro}g/L and 1.16 {micro}g/L. Furthermore, projecting these results to the population level suggests that exposure to DBP from early embryonic development leads to a decrease in growth rate and a change in population structure.

physiology↗

bioRxiv2024

Cluefish: mining the dark matter of transcriptional data series with over-representation analysis enhanced by aggregated biological prior knowledge

Interpreting transcriptomic data presents significant challenges, particularly in non-targeted approaches. While modern functional enrichment methods are well-suited for experimental designs involving two conditions, they are less applicable to data series. In this context, we developed Cluefish, a free and open-source, semi-automated R workflow designed for untargeted, comprehensive biological interpretation of transcriptomic data series. Cluefish applies over-representation analysis on pre-clustered protein-protein interaction networks, using clusters as anchors to identify smaller, more specific biological functions. Innovative features, including cluster merging and recovery of isolated genes through shared biological contexts, enable a more complete exploration of the data. We applied Cluefish to an in-house dataset with zebrafish exposed to a dose-gradient of dibutyl phthalate, and to two published toxicology datasets featuring different organisms. Combined with DRomics, a tool for dose-response analysis--Cluefish identified gene clusters deregulated at low doses and linked to biological functions overlooked by the standard approach. Notably, it revealed that retinoid signalling disruption may be the most sensitive pathway affected by dibutyl phthalate during zebrafish development, potentially leading to morphological changes. The Cluefish workflow aims to provide valuable clues for biological hypothesis generation and experimental validation. It is freely available at https://github.com/ellfran-7/cluefish. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/627334v2_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@19d9903org.highwire.dtl.DTLVardef@1a8a118org.highwire.dtl.DTLVardef@1e84c3aorg.highwire.dtl.DTLVardef@1e4ac35_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2024

Proteomic analysis of the pyrenoid-traversing membranes of Chlamydomonas reinhardtii reveals novel components

O_LIPyrenoids are algal CO2-fixing organelles that mediate approximately one-third of global carbon fixation. Most pyrenoids are traversed by membranes that are thought to supply them with concentrated CO2. Despite the critical nature of these membranes for pyrenoid function, they are poorly understood, with few protein components known in any species. C_LIO_LIHere, we identify protein components of the pyrenoid-traversing membranes from the leading model alga, Chlamydomonas reinhardtii, by affinity purification and mass spectrometry of membrane fragments. Our proteome includes previously-known proteins as well as novel candidates. C_LIO_LIWe further characterize two of the novel pyrenoid-traversing membrane-resident proteins: Cre10.g452250, which we name Pyrenoid Membrane Enriched 1 (PME1), and Cre02.g143550, also known as Low-CO2-Induced 16 (LCI16). We confirm the pyrenoid-traversing membrane localization of LCI16 and observe that PME1 and LCI16 physically interact. We find that neither protein is required for normal membrane morphology or growth under CO2-limiting conditions, but that both mutants show a similar proteomic profile to those of established pyrenoid mutants. C_LIO_LITaken together, our study identifies the proteome of the pyrenoid-traversing membranes and initiates the characterization of a novel pyrenoid-traversing membrane complex, building toward a mechanistic understanding of the pyrenoid. C_LI

molecular biology↗

bioRxiv2024

Biogenesis, engineering and function of membranes in the CO2-fixing pyrenoid

Summary ParagraphApproximately one-third of global CO2 assimilation is performed by the pyrenoid1, a liquid-like organelle found in most algae and some plants2. Specialized membranes are hypothesized to drive CO2 assimilation in the pyrenoid by delivering concentrated CO23,4, but their biogenesis and function have not been experimentally characterized. Here, we show that homologous proteins SAGA1 and MITH1 mediate the biogenesis of the pyrenoid membrane tubules in the model alga Chlamydomonas reinhardtii and are sufficient to reconstitute pyrenoid-traversing membranes in a heterologous system, the plant Arabidopsis thaliana. SAGA1 localizes to the regions where thylakoid membranes transition into tubules and is necessary to initiate tubule formation. MITH1 localizes to the tubules and is necessary for their extension through the pyrenoid. Tubule-deficient mutants exhibit growth defects under CO2-limiting conditions, providing evidence for the function of membrane tubules in CO2 delivery to the pyrenoid. Furthermore, these mutants form multiple aberrant condensates of pyrenoid matrix, indicating that a normal tubule network promotes the coalescence of a single pyrenoid. The reconstitution of pyrenoid-traversing membranes in a plant represents a key milestone toward engineering a functional pyrenoid into crops for improving crop yields. More broadly, our study demonstrates the functional importance of pyrenoid membranes, identifies key biogenesis factors, and paves the way for the molecular characterization of pyrenoid membranes across the tree of life.

molecular biology↗

bioRxiv2022

Comparing Machine Learning Architectures for the Prediction of Peptide Collisional Cross Section

1Mass spectrometry is the method of choice in large-scale proteomics studies. One common method is data-independent acquisition (DIA), which allows for high-throughput analysis of biological samples, but also produces complex data. Methods of peptide separation, in addition to retention time, improve data analysis and there has been increasing interest in separating peptides based on collisional cross section (CCS), which is a measure of the size of a peptide. However, existing libraries that are used during data analysis lack CCS measurements, and this data is expensive and time-consuming to acquire. This has led to the desire to predict library values for mass spectrometry analysis. Here we compare three deep learning architectures, LSTM, CNN, and transformer, for the tasks of retention time and collisional cross section prediction. We show that the LSTM and CNN models perform similarly and that the transformer has a lower performance than expected.

bioinformatics↗