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Results for “molecular biology”

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bioRxiv2023

One-pot Golden Gate Assembly of an avian infectious bronchitis virus reverse-genetics system

Avian infectious bronchitis is an acute respiratory disease of poultry of particular concern for global food security. Investigation of Infectious Bronchitis Virus (IBV), the causative agent of avian infectious bronchitis, via reverse genetics enables deeper understanding of virus biology and a rapid response to emerging variants. Classic methods of reverse genetics for IBV can be time consuming, rely on recombination for the introduction of mutations, and, depending on the system, can be subject to genome instability and unreliable success rates. In this study, we have applied data-optimized Golden Gate Assembly design to create a rapidly executable, flexible, and faithful reverse genetics system for IBV. The IBV genome was divided into 12 fragments at high-fidelity fusion site breakpoints. All fragments were synthetically produced and propagated in E. coli plasmids, amenable to standard molecular biology techniques for DNA manipulation. The assembly can be carried out in a single reaction, with the products used directly in subsequent viral rescue steps. We demonstrate the use of this system for generation of point mutants and gene replacements. This Golden Gate Assembly-based reverse genetics system will enable rapid response to emerging variants of IBV, particularly important to vaccine development for controlling spread within poultry populations.

genetics↗

bioRxiv2024

ChemGLaM: Chemical-Genomics Language Models for Compound-Protein Interaction Prediction

Deep learning-based compound-protein interaction (CPI) prediction models are promising in the field of molecular biology, particularly for facilitating the drug discovery process. In practical applications, CPI models should achieve a high generalization performance, quantify prediction confidence, and ensure explainability. Here, we propose ChemGLaM, a chemical genomics language model for reliable and explainable CPI predictions, by addressing these three crucial aspects. ChemGLaM integrates independently pre-trained chemical and protein language models through an interaction block with a cross-attention mechanism, achieving state-of-the-art performance in predicting novel CPIs. Incorporating uncertainty estimation and attention visualization enables ChemGLaM to enhance the success rate of virtual screening and to provide molecular insights into CPIs. Furthermore, we demonstrate its practical applicability by constructing a public database for large-scale CPI predictions and enabling drug/target exploration for candidate treatment of amyotrophic lateral sclerosis (ALS). ChemGLaM represents a significant step toward overcoming the challenges of AI-driven drug discovery and addressing unmet medical needs.

bioinformatics↗

bioRxiv2024

Reversible and reusable compartmentalized microfluidic chip for coculture of dorsal root ganglion neurons

Compartmentalized microfluidic chips play an important role in understanding the cellular mechanisms involved in neurodegenerative disorders. Dorsal root ganglia are a well-established model for modelling the peripheral nervous system (PNS), but their development on a chip remains limited. Furthermore, it would be beneficial for the devices to be openable in order to access the biological material inside for analyses. Easy to prototype and biocompatible, styrenic block copolymers (SBC) are an alternative to polydimethylsiloxane (PDMS) that offer both reversible and permanent bonding properties. This paper presents a fast and straightforward method to produce compartmentalized SBC chips. The study validates the culture of murine dorsal root ganglia explants, comparing it to the standard methods, to obtain a model of the PNS. Moreover, the reversible bonding properties of the SBC permit the reuse of the chip with a quick and easy cleaning protocol. It provides direct access to the cells, opening the way for imaging and molecular biology analysis. The comparison of the resources required to produce PDMS and SBC chips highlights the importance of moving to reusable devices. These detachable, easy-to-manufacture and sustainable all-thermoplastic platforms provide an alternative way of prototyping compartmentalized devices for in vitro PNS modeling.

biophysics↗

bioRxiv2020

Glycosyltransferase POMGNT1 deficiency affects N-cadherin-mediated cell-cell adhesion

Defects in protein O-mannosylation lead to severe congenital muscular dystrophies known as -dystroglycanopathy. A hallmark of these diseases is the loss of the O-mannose-bound matriglycan on -dystroglycan, which leads to a reduction in cell adhesion to the extracellular matrix. Mutations in protein O-mannose {beta}1,2-N-acetylglucosaminyltransferase 1 (POMGNT1), which is crucial for the elongation of O-mannosyl glycans, are mainly associated with muscle-eye-brain (MEB) disease. In addition to defects in cell-extracellular matrix adhesion, aberrant cell-cell adhesion has occasionally been observed in response to defects in POMGNT1. However, direct molecular mechanisms are largely unknown. We used POMGNT1 knock-out HEK293T cells and fibroblasts from a MEB patient to gain a deeper insight into the molecular changes in POMGNT1 deficiency. A combination of biochemical and molecular biological techniques with proteomics, glycoproteomics and glycomics revealed that a lack of POMGNT1 activity strengthens cell-cell adhesion. We demonstrate that the altered intrinsic adhesion properties are due to an increased abundance of N-cadherin (N-Cdh). In addition, site-specific changes in the N-glycan structures in the extracellular domain of N-Cdh were detected, which positively impact on homotypic interactions. We found that in POMGNT1 deficient cells ERK1/2 and p38 signaling pathways are activated and transcriptional changes that are comparable to the epithelial-mesenchymal transition (EMT) are triggered, defining a possible molecular mechanism underlying the observed phenotype. Our study indicates that changes in cadherin-mediated cell-cell adhesion and other EMT-related processes may contribute to the complex clinical symptoms of MEB or -dystroglycanopathy in general, and suggests a previously underestimated impact of changes in O-mannosylation on N-glycosylation.

biochemistry↗

bioRxiv2022

Multiomics analyses reveal the central role of nucleolus and nucleoid machinery during heat stress acclimation in Pinus radiata

Climate warming is causing quick changes in mean annual temperature and more severe drought period. These are major contributors of forest dieback, which is becoming more frequent and widespread, particularly in warm and drought-prone regions. Despite being a hot topic in non-woody plant sciences, the information about how heatwaves impact in tree molecular biology is still scarce. In this work we investigated how the transcriptome of Pinus radiata changes during initial stress response and stress acclimation. To this end, and considering this species is non sequenced, we generated a deep dataset employing Illumina technology. This approach allowed us to reconstruct 77335 contigs which were annotated following gene ontology, and to define 12164 and 13590 transcripts as down- and upregulated, respectively, across the three sampled experimental points. Enrichment analysis allowed to distinguish 9 down-regulated pathways, the most of them related to the reduction of apoplast, and water transport. While 22 were upregulated, which followed two different trends those pathways that peaks at short-term (acute response) from those which accumulated long-term (acclimation response) being most of them related to heat shock response, redox machinery and RNA processing. Additionally, the combination of transcriptome data with other available omics layers, allowed an exceptional understanding of the mechanisms behind heat stress response, involving complex interrelated processes from molecular to physiological level. Nucleolus and nucleoid activities seem to be a central core in acclimating process, producing specific RNA isoforms and other essential elements for anterograde-retrograde stress signaling as NAC proteins, Helicase RVB, RZ1 RNA chaperone, or ribosomal RPS4. These mechanisms are connected by elements already known in heat stress-response (redox, heat shock proteins or ABA-related). But also, novel candidates, as photosynthetic pigments, shikimate, or proline centric proteases activities, have been identified effectively networking biochemical responses to its potential regulatory element. This work provides a first deep overview about what molecular mechanisms underlying heat stress response and acclimation in pines, supporting the development of new breeding strategies to face the challenges that the climate change will impose to forests.

plant biology↗

bioRxiv2019

An electrostatic-interaction-based mechanism triggering misfolding of prion proteins from cellular isoform to scrapie isoform

Understanding how prion proteins refold from a cellular isoform (PrPC) to a disease-causing isoform (PrPSc) has been among the "ultimate challenges" in molecular biology, biophysics, pathology, and immunology. Conformational changes of prion proteins from PrPC to PrPSc involve the unfolding of a short -helix that overshadows the challenge. Considering the mechanisms of electrostatic attraction, thermal disturbance, hydrogen ion concentration, hydrophobic interaction, and the shielding effect of water molecules, this study reveals an electrostatic-interaction-based mechanism by means of which prion proteins refold in an aqueous environment. The electrostatic-interaction-induced protein unfolding mechanism causes a hydrophobic polypeptide segment to dangle out over the conglobate main body of the prion protein, thereby allowing the first triangular hydrophobic rung formation via hydrophobic interaction. A molecular model of PrPSc is proposed that allows the {beta}-solenoid with a triangular hydrophobic core. Statement of SignificanceWe present three main results that would revolutionize the understanding of pathology of prion diseases. First, the prion protein refolding (from cellular isoform to scrapie isoform) derives from the unfolding of the shortest -helix of PrPC, which provides a long polypeptide segment full of hydrophobic residues dangling out over the conglobate main body of the prion protein, thereby allowing formation of the first triangular hydrophobic rung via hydrophobic interaction. Second, polyanions-induced increasing in local concentration of hydrogen ion (i.e., the PH increase) undermines the shielding effect of water molecules, thereby allowing escape of the arginine side chains from the hydration shell, destabilizing the shortest -helix and initiating the refolding of PrPC. Third, a {beta}-solenoid structural model for PrPSc with a triangular hydrophobic core is proposed.

biophysics↗

bioRxiv2026

Joint protein, mRNA and DNA sequence design and optimization with nucleotide-level Potts models

Protein design typically generates amino acid sequences first and then translates them into DNA post-hoc limiting control over the nucleotide sequence via codon choice at design time. We introduce NuCaliby, a structure-conditioned model that jointly designs amino acid, mRNA, and DNA sequences of a protein at nucleotide resolution. NuCaliby predicts a Potts model over a nucleotide graph, trained using amino acid supervision by marginalizing over synonymous codons. It preserves residue-level designability on par with the original Caliby model. Its energy-based formulation supports composable inference-time guidance from sequence-level objectives through proposal construction and candidate acceptance, allowing the incorporation of biological proxies into the coding nucleotide sequence. Under organism-specific tRNA adaptation guidance, NuCaliby improves adaptation to host tRNA pools beyond synonymous sequence space, trading-off self-consistency. NuCaliby also embeds specified RNA motif sequences directly into coding sequences, avoiding the combinatorial growth required for the same task at the amino-acid level. In wet lab experiments, NuCaliby produces expressible and soluble proteins on par with state of the art methods, while enabling more complex nucleotide-level control and optimization. Together, these results extend protein design beyond the amino acid level, enabling joint optimization across the central dogma of molecular biology. The code and model weights are available here: https://github.com/blazejba/NuCaliby

biophysics↗

bioRxiv2019

Comparative analyses of saprotrophy in Salisapilia sapeloensis and diverse plant pathogenic oomycetes reveal lifestyle-specific gene expression

Oomycetes include many well-studied, devastating plant pathogens. Across oomycete diversity, plant-infecting lineages are interspersed by non-pathogenic ones. Unfortunately, our understanding of the evolution of lifestyle switches is hampered by a scarcity of data on the molecular biology of saprotrophic oomycetes, ecologically important primary colonizers of dead tissue that can serve as informative reference points for understanding the evolution of pathogens. Here, we established Salisapilia sapeloensis growing on axenic litter as a tractable system for the study of saprotrophic oomycetes. We generated multiple transcriptomes from S. sapeloensis and compared them to (a) 22 oomycete genomes and (b) the transcriptomes of eight pathogenic oomycetes grown under 13 conditions (three pathogenic lifestyles, six hosts/substrates, and four tissues). From these analyses we obtained a global perspective on the gene expression signatures of oomycete lifestyles. Our data reveal that oomycete saprotrophs and pathogens use generally similar molecular mechanisms for colonization, but exhibit distinct expression patterns. We identify S. sapeloensis specific array and expression of carbohydrate-active enzymes and regulatory differences in pathogenicity-associated factors, including the virulence factor EpiC2B. Further, S. sapeloensis was found to express only a small repertoire of effector genes. In conclusion, our analyses reveal lifestyle-specific gene regulatory signatures and suggest that, in addition to variation in gene content, shifts in gene regulatory networks might underpin the evolution of oomycete lifestyles.

microbiology↗

bioRxiv2018

A new framework for the study of apicomplexan diversity across environments

Apicomplexans are a group of microbial eukaryotes that contain some of the most well-studied parasites, including widespread intracellular pathogens of mammals such as Toxoplasma and Plasmodium (the agent of malaria), and emergent pathogens like Cryptosporidium and Babesia. Decades of research have illuminated the pathogenic mechanisms, molecular biology, and genomics of model apicomplexans, but we know surprisingly little about their diversity and distribution in natural environments. In this study we analyze the distribution of apicomplexans across a range of both host-associated and free-living environments, covering animal hosts from cnidarians to mammals, and ecosystems from soils to fresh and marine waters. Using publicly available small subunit (SSU) rRNA gene databases, high-throughput environmental sequencing (HTES) surveys such as Tara Oceans and VAMPS, as well as our own generated HTES data, we developed an apicomplexan reference database, which includes the largest apicomplexan SSU rRNA tree available to date and encompasses comprehensive sampling of this group and their closest relatives. This tree allowed us to identify and correct incongruences in the molecular identification of sequences, particularly within the hematozoans and the gregarines. Analyzing the diversity and distribution of apicomplexans in HTES studies with this curated reference database also showed a widespread, and quantitatively important, presence of apicomplexans across a variety of free-living environments. These data allow us to describe a remarkable molecular diversity of this group compared with our current knowledge, especially when compared with that identified from described apicomplexan species. This revision is most striking in marine environments, where potentially the most diverse apicomplexans apparently exist, but have not yet been formally recognized. The new database will be useful for both microbial ecology and epidemiological studies, and provide valuable reference for medical and veterinary diagnosis especially in cases of emerging, zoonotic, and cryptic infections.\n\nAuthor SummaryApicomplexans are important animal and human parasites, but little is known about their distribution and diversity in the natural environment. We have developed a phylogenetically informed and manually curated reference database for the SSU rRNA barcode gene, and analyzed all publicly available sequences from a broad range of environments, providing a needed framework to analyze high-throughput environmental sequencing (HTES) data. The reference database and the amplicon sequences identified a striking diversity of apicomplexans in the environment, including habitats not usually associated with this group (e.g. open ocean). The phylogenetic framework will underpin microbial ecology studies and provide valuable resources for medical and veterinary biology.

microbiology↗

bioRxiv2017

Subharmonics And Chaos In Simple Periodically-Forced Biomolecular Models

This paper uncovers a remarkable behavior in two biochemical systems that commonly appear as components of signal transduction pathways in systems biology. These systems have globally attracting steady states when unforced, so they might have been considered \"uninteresting\" from a dynamical standpoint. However, when subject to a periodic excitation, strange attractors arise via a period-doubling cascade. Quantitative analyses of the corresponding discrete chaotic trajectories are conducted numerically by computing largest Lyapunov exponents, power spectra, and autocorrelation functions. To gain insight into the geometry of the strange attractors, the phase portraits of the corresponding iterated maps are interpreted as scatter plots for which marginal distributions are additionally evaluated. The lack of entrainment to external oscillations, in even the simplest biochemical networks, represents a level of additional complexity in molecular biology, which has previously been insufficiently recognized but is plausibly biologically important.

systems biology↗

bioRxiv2025

Development of charged nanobubble-containing media and their effects on iPSC-derived cell cultures

Nanobubbles (NBs) are gas-filled spherical structures less than 1 {micro}m in diameter, characterized by high surface charge, long-term stability, and the ability to generate bactericidal hydroxyl radicals upon collapse. Although these unique properties enable their extensive applications, including wastewater treatment, their cell biological applications at neutral pH remain limited by difficulties in maintaining stability and surface charge. Here, we succeeded in generating both positively and negatively charged NBs, achieving high zeta potentials in human iPSC-derived neural progenitor cell (NPC) and neuron culture media (pH 7.4). Similar to their bactericidal effects, NBs induced cell death in iPSC-derived cells, with positively charged NBs showing stronger cytotoxicity than negatively charged ones. This may be because the cell membrane carries a negative charge, making positively charged NBs more likely to approach and interact with the membrane, or because positively charged nanobubbles exhibit stronger radical generation. In future, we aim to elucidate the molecular biological mechanisms underlying NB-induced cell death and to contribute to the potential application of nanobubbles in regenerative medicine. This study will serve as an initial step toward that goal.

bioengineering↗

bioRxiv2025

Generative continuous time model reveals epistatic signatures in protein evolution

Protein evolution is fundamentally shaped by epistasis, where the effect of a mutation depends on the sequence context. As standard phylogenetic methods assume independently evolving sites, there is a need for more complex models based on accurate estimations of the fitness landscape. Good candidates are modern generative models - such as the Potts model - which successfully capture epistatic effects. However, recent works on generative evolutionary models usually use discrete time, making them difficult to integrate with the standard frameworks in evolutionary biology. We introduce a continuous-time sequence evolution model using the Gillespie algorithm and parameterized by a generative Potts model. This approach enables us to simulate realistic, family-specific evolutionary trajectories and allows for direct comparison with independent-site models. Surprisingly, we find that while epistasis significantly slows down evolution, it does not change the average evolutionary rates at individual sites. This is explained by the rate heterogeneity caused by context-dependence: we show that the rate at some positions varies between null to high values depending on the context, while other positions are essentially independent from the context. Finally, we show that epistasis leads to a systematic underestimation bias in the inference of evolutionary distance between sequences. Overall, our work provides a new tool for simulating realistic protein evolution and offers novel insights into the complex interplay between epistasis and evolutionary dynamics. Significance statementUnderstanding how proteins evolve is central to molecular biology and phylogenetics. Traditional evolutionary models assume that mutations act independently at each position in a sequence. This neglects epistasis -- the fact that the effect of a mutation depends on the rest of the sequence -- which is known to be ubiquitous in proteins. By simulating protein evolution in continuous time using a generative model, our approach produces realistic sequences and reveals how epistasis shapes evolutionary dynamics. We find that epistasis slows down evolution and can mislead common methods for estimating evolutionary timescales. This work bridges modern generative models of proteins and phylogenetics, providing new tools to better understand molecular evolution.

bioinformatics↗

bioRxiv2018

MORPHOMETRIC IDENTIFICATION OF STEM BORERS Diatraea saccharalis AND Diatraea busckella (Lepidoptera: Crambidae) IN SUGARCANE CROPS (Saccharum officinarum) IN CALDAS DEPARTMENT, COLOMBIA

The sugarcane (Saccharum sp.), of great importance for being one of the most traditional rural agroindustries in Latin America and the Caribbean, as part of the agricultural systems, is vulnerable to increases or reductions in the incidence of pests associated with extreme events of climate change, such as prolonged droughts, hurricanes, heavy and out of season rains, among others, contributing to the increase losses in agricultural production, which forces farmers to make excessive expenditures on pesticides that generally fail to solve the issue. (Vazquez, 2011). The main pest belongs to the Diatraea complex (Vargas et al., 2013; Gallego et al., 1996), a larval stage perforator habit. Different field evaluations have revealed the presence of a species that had not been reported in sugarcane crops, Diatraea busckella, and to corroborate the finding, a method of identification was needed whose advantage was to be quick and also low cost, in this sense, geometric morphometry is a mathematical tool with biological basis (Bookstein, 1991), which allows to decompose the variation resulting from the physiology of individuals of the most stable individuals of the population, product of the genetic component. CLIC (Collecting Landmarks for Identification and Characterization) was used for identification, with reference to the previous right wing (De La Riva et al., 2001; Belen et al., 2004; Schachter-Broide et al., 2004; Dvorak et al., 2006; Soto Vivas et al., 2007). Wing morphometry was performed using generalized Procrustes analysis (Rohlf and Marcus, 1993). The analysis clearly differentiated between D. busckella and D. saccharalis, eliminating the environmental factors that could generate some level of error, being considered a support tool that validates the molecular biology processes for the identification of organisms.

ecology↗

bioRxiv2019

A window into lysogeny: Revealing temperate phage biology with transcriptomics

Integrated phage elements, known as prophages, are a pervasive feature of bacterial genomes. Prophages can enhance the fitness of their bacterial hosts by conferring beneficial functions, such as virulence, stress tolerance or phage resistance, which are encoded by accessory loci. Whilst the majority of phage-encoded genes are repressed during lysogeny, accessory loci are often highly expressed. However, novel prophage accessory loci are challenging to identify based on DNA sequence data alone. Here, we use bacterial RNA-seq data to examine the transcriptional landscapes of five Salmonella prophages. We show that transcriptomic data can be used to heuristically enrich for prophage features that are highly expressed within bacterial cells and often represent functionally-important accessory loci. Using this approach we identify a novel anti-sense RNA species in prophage BTP1, STnc6030, which mediates superinfection exclusion of phage BTP1 and immunity to closely-related phages. Bacterial transcriptomic datasets are a powerful tool to explore the molecular biology of temperate phages.

microbiology↗

bioRxiv2026

Rational Design of a Photoactivated Fluorescent Probe for Thiol-ene Mediated Protein Labelling

Fluorescent labelling of biomolecules enables the visualization and tracking of molecular processes in cells, providing insights into cellular function and disease mechanisms. Despite recent advances in bioorthogonal labelling, efficient and site-selective strategies for targeting alkene functionalities remain limited. Here, we report AbzSH, a compact aminobenzamide-based fluorescent thiol probe for selective alkene labelling through thiol-ene ligation. Photoinduced ligation proceeds under mild, radical-mediated conditions in aqueous media and exhibits broad substrate compatibility, including carbohydrate, amino acid, and steroid scaffolds. The method is readily extended to protein labelling, enabling selective modification of both chemically functionalized proteins and engineered proteins containing genetically encoded alkene motifs. Efficient and chemoselective labelling was further demonstrated in complex cell lysates, highlighting the robustness of the approach in biologically relevant environments. Collectively, these results establish AbzSH as a versatile fluorescent probe for alkene-directed biomolecular labelling and provide a broadly applicable platform for chemical biology, molecular imaging, proteomics, and drug discovery.

biochemistry↗

bioRxiv2023

Covering Hierarchical Dirichlet Mixture Models on binary data to enhance genomic stratifications in Onco-Hematology

Onco-hematological studies are increasingly adopting statistical mixture models to support the advancement of the genetically-driven classification systems for blood cancer. Targeting enhanced patients stratification based on the sole role of molecular biology attracted much interest and contributes to bring personalized medicine closer to reality. In particular, Dirichlet processes have become the preferred method to approach the fit of mixture models. Usually, the multinomial distribution is at the core of such models. However, despite their advanced statistical formalism, these processes are not to be considered black box techniques and a better understanding of their working mechanisms enables to improve their employment and explainability. Focused on genomic data in Acute Myeloid Leukemia, this work unfolds the driving factors and rationale of the Hierarchical Dirichlet Mixture Models of multinomials on binary data. In addition, we introduce a novel approach to perform accurate patients clustering via multinomials based on statistical considerations. The newly reported adoption of the Multivariate Fishers Non-Central Hypergeometric distributions reveals promising results and outperformed the multinomials in clustering both on simulated and real onco-hematological data. Author summaryExplainable models are particularly attractive nowadays since they have the advantage to convince clinicians and patients. In this work we show that a deeper understanding of the Hierarchical Dirichlet Mixture Model, a non-black box method, can lead to better data modelling. In onco-hematology Hierarchical Dirichlet Mixture Models typically help to cluster molecular alterations rather than patients. Here, an intuitive statistical approach is presented to tackle patient classification based on the Hierarchical Dirichlet Mixture Models outcome. Additionally, molecular alterations are usually modelled by Hierarchical Dirichlet Mixture Models as a mixture of multinomial distributions. This work highlights that the alternative Fishers Non-Central Hypergeometric distribution can provide even better results and can give a higher priority to rare molecular alterations for patient classification.

cancer biology↗

bioRxiv2023

The macronuclear genomic landscape within Tetrahymena thermophila

The extent of intraspecific genomic variation is key to understanding species evolutionary history, including recent adaptive shifts. Intraspecific genomic variation remains poorly explored in eukaryotic microorganisms, especially in the nuclear dimorphic ciliates, despite their fundamental role as laboratory model systems and their ecological importance in many ecosystems. We sequenced the macronuclear genome of 22 laboratory strains of the oligohymenophoran Tetrahymena thermophila, a model species in both cellular biology and evolutionary ecology. We explored polymorphisms at the junctions of programmed eliminated sequences, and reveal their utility to barcode very closely related cells. As for other species of the genus Tetrahymena, we confirm micronuclear centromeres as gene diversification centres in T. thermophila, but also reveal a two-speed evolution in these regions. In the rest of the genome, we highlight recent diversification of genes encoding for extracellular proteins and cell adhesion. We discuss all these findings in relation with ciliates ecology and cellular characteristics. Impact StatementThis is the first study of population genomics in the ciliate Tetrahymena thermophila. This bacterivore species plays an important role in aquatic trophic chains and is widely used as a model in cell and molecular biology, ecology, evolution or toxicology. As all ciliates, it contains a germline micronucleus and a somatic macronucleus. Sequencing of the macronucleus reveals that the centromeric region of the micronucleus are simultaneously a region of new gene diversification, as observed in other Tetrahymena species, and a region containing highly conserved genes. The results also confirm that the formation of the macronucleus from the micronucleus is highly imprecise. Interestingly, this process generates a genomic barcode that can discriminate cells derived from a given sexual reproduction event, allowing to study more finely population dynamics/history in nature. Data summaryAll data are fully provided in Supplementary Materials. The raw data of the 22 Tetrahymena genomes have been deposited in the Sequence Read Archive (https://www-ncbi-nlm-nih-gov.inee.bib.cnrs.fr/bioproject/PRJNA1012331). Accession numbers are listed in Table S1 (available in the online version of this article).

genomics↗

bioRxiv2024

Exploring environmental microfungal diversity through serial single cell screening

Known for its remarkable diversity and ecological importance, the fungal kingdom remains largely unexplored. In fact, the number of unknown and undescribed fungi is predicted to exceed the number of known fungal species by far. Despite efforts to uncover these dark fungal taxa, we still face inherent sampling biases and methodological limitations. Here, we present a framework that combines taxonomic knowledge, molecular biology, and data processing to explore the fungal biodiversity of enigmatic aquatic fungal lineages. Our work is based on serial screening of environmental fungal cells to approach unknown fungal taxa. Microscopic documentation is followed by DNA analysis of laser micro-dissected cells, coupled with a ribosomal operon barcoding step realized by long-read sequencing, followed by an optional whole genome sequencing step. We tested this approach on a range of aquatic fungal cells mostly belonging to the group of aquatic hyphomycetes derived from environmental samples. From this initial screening, we were able to identify thirty-two potentially new fungal taxa in the target dataset. By extending this methodology to other fungal lineages associated with different habitats, we expect to increasingly characterize the molecular barcodes of dark fungal taxa in diverse environmental samples. This work offers a promising solution to the challenges posed by unknown and unculturable fungi and holds the potential to be applied to the diverse lineages of undescribed microeukaryotes.

microbiology↗