ABSTRACT Mitochondrial DNA (mtDNA) can exist in homoplasmic or heteroplasmic states, but the dynamics and stability of heteroplasmy remain poorly understood in fungal plant pathogens. Because a key fungicide target (cytochrome b ) is encoded in the mitochondrial genome, understanding these mtDNA dynamics is crucial for predicting resistance development and evolution in agricultural pathosystems. In Zymoseptoria tritici, mutations G143A and Y132C in the quinone outside inhibitor-binding site of the cytochrome b subunit confer a high level of resistance to the fungicides pyraclostrobin and metyltetraprole, respectively. Under fungicide selection, these mutations were observed to coexist only transiently. Using experimental evolution and single-cell analysis, we demonstrate the presence of a temporarily heteroplasmic state in which both G143A and Y132C alleles coexist within individual cells at variable ratios. Allele predominance within the heteroplasmic populations shifted rapidly in response to fungicide pressure, resulting in a mitochondrial mutation switch that ultimately led to either G143A or Y132C homoplasmy. This finding provides evidence that transient heteroplasmy represents a critical intermediate phase during the transition between resistance genotypes in Z. tritici . To our knowledge, this is the first single-cell demonstration of mitochondrial heteroplasmy in a pathogenic fungus, offering new insights into mitochondrial genome dynamics that shape adaptive responses to fungicides. IMPORTANCE Mitochondrial genomes in fungal pathogens are generally considered to be genetically uniform. However, our work shows that mitochondrial heteroplasmy can form a transient and unstable state that enables switching between resistance-associated haplotypes under changing selective pressures. Using single-cell analysis, we demonstrate that individual cells harbor varying proportions of resistance alleles, which can rapidly shift depending on fungicide exposure. These findings provide new insight into how mitochondrial genome dynamics contribute to microbial adaptation and highlight a previously underappreciated mechanism that may influence the emergence and development of antifungal resistance.
ABSTRACT Understanding how interspecific interactions shape ecosystem functioning is a fundamental and longstanding question in ecology, especially along an evolutionary trajectory. Here, we used experimental evolution to evaluate how microbial interactions and adaptive mutations shaped community-level functions in synthetic denitrifying communities (SDCs) along a species richness gradient (one, two, and six species). Our results showed that competitive microbial interactions were observed and significantly ( P < 0.05) enhanced denitrification rates in the six-species SDCs during experimental evolution. Genome and metagenome re-sequencing analysis revealed the highest fixed non-synonymous and frameshift mutations within the six-species SDCs, among genes involved in nutrient transport, DNA repair, and secretion pathways. AlphaFold2 protein structure prediction, molecular docking, and Evo 2 host fitness prediction indicated that the fixed mutations could improve host strain fitness, and partial least squares path modeling (PLS-PM) further revealed that interspecific competition accelerated adaptive mutations, thereby reinforcing community-level functions, indicating potential Red Queen dynamics. This study offers novel insights into our understanding of eco-evolutionary mechanisms linking species richness, microbial interactions, adaptive mutations, and community functions, with important implications for active nitrogen removal and greenhouse gas mitigation in diverse ecosystems. IMPORTANCE Microbial diversity is widely recognized as a key driver of ecosystem functioning, yet how species interactions shape ecosystem functions through evolutionary processes remains poorly understood. Using synthetic denitrifying communities with different levels of species richness, we show that interspecific competition can accelerate adaptive mutations and enhance community-level denitrification over evolutionary timescales. Communities with higher species richness accumulated more adaptive mutations, particularly in genes associated with nutrient transport, DNA repair, and secretion systems, ultimately improving microbial fitness and denitrification performance. Our findings provide direct experimental evidence that microbial competition can promote functional adaptation, consistent with the Red Queen hypothesis. This study advances our understanding of the eco-evolutionary mechanisms linking species richness, microbial interactions, adaptive evolution, and ecosystem functioning.
ABSTRACT Suppressive antiretroviral therapy (ART) in people with HIV (PWH) arrests progression to AIDS and onward viral transmission. However, viral transcription from integrated HIV-1 proviruses persists on treatment and is linked to markers of chronic immune activation, contributing to the accelerated development of comorbidities in PWH. Of particular interest are persistent responses in long-lived tissue-resident myeloid cells, which direct tissue-level inflammatory processes through cytokine secretion and interactions with other immune cell populations. Here, we review recent findings on viral nucleic acid sensing events in HIV-infected myeloid cells to shed light on possible mechanisms of persistent inflammation resulting from chronic HIV-1 transcription in myeloid cells in PWH.
ABSTRACT Microsporidia such as Encephalitozoon hellem are obligate intracellular human parasites that remain genetically intractable, limiting the functional characterization of their proteomes. Experimental structural studies are challenging, as many proteins in microsporidia comprise a large percentage of disordered regions. Computational structural studies based on homology-based modeling and the use of deep-learning algorithms for microsporidian proteins also remain limited because most have little to no sequence similarity to proteins with solved structures. To address these limitations, we developed an approach that incorporates cross-linking mass spectrometry (XL-MS) data into structure prediction. XL-MS data provide upper-bound distance constraints that can be incorporated into protein deep-learning-based modeling and subsequent docking. Using this approach, we generated a model of two interacting E. hellem spore wall proteins, spore wall protein 1B (Swp1b) and endospore protein 1 (EnP1), which have no clear homologs outside of microsporidia and contain several disordered regions. These proteins are abundant spore wall proteins of microsporidia and previously were not known to interact with one another. The resulting model not only is consistent with the experimental cross-links used to generate the model but was also subsequently confirmed by independently generated XL-MS data. The described AlphaLink-Modeller framework for structure prediction is particularly well suited to proteins with limited homology and/or substantial flexible regions, given that they adopt a defined structural state within a biological context, thereby extending integrative modeling approaches to previously inaccessible targets. IMPORTANCE In this article, we demonstrate an improved method for the prediction of the structure of protein complexes with no clear homologs and a considerable number of disordered regions. This is significant because these types of proteins are critical to understanding the biology of organisms, yet model generation of these classes has been inaccessible. The method incorporates experimental data obtained from cross-linking mass spectrometry (XL-MS) into the modeling process, providing a method to integrate such experimental data into computational modeling of the structure of proteins and protein interactions. For this paper, we have used this method for predicting the structure of two highly abundant Encephalitozoon hellem proteins in the spore wall that are important for host cell infection due to this pathogen of humans and other vertebrates.
ABSTRACT Members of Marine Group IV, now termed Hikarchaeia, hold an important transitional evolutionary position among Archaea but remain uncultivated, and their ecology remains uncharacterized. Over a 5-year period, we performed monthly profile sampling in the North Atlantic Subtropical Gyre and sequenced V4 16S rRNA gene amplicons, while also collecting additional size-fractionated and metagenomic samples. Hikarchaeal relative abundance annually peaked at ~1% of prokaryotic amplicons. Their relative abundances were significantly higher after deep winter mixing when thermal stratification isolated exported dissolved organic matter in the twilight zone (TZ), the boundary region between the epipelagic and mesopelagic. A diminutive 1.17 Mbp complete hikarchaeal genome was recovered by sequencing and co-assembling diel TZ metagenomes from 200 m during summer, where their relative abundances were highest. Phylogenomic reconstruction incorporating our new metagenome-assembled genome (MAG) and public MAGs established five clades. Clades I and III were in subtropical and tropical environments, with vertical partitioning: Clade I dominated the TZ, and Clade III detection initiated in the lower mesopelagic and extended into the bathypelagic. Clade V is polar-associated. Data sparsity makes Clade II and IV distributions unclear. All Hikarchaeia recovered thus far appear to be free-living aerobes capable of heterotrophy. Unlike MGI, MGII, and MGIII Archaea, and most marine pelagic bacteria, the Hikarchaeia encode bacterioruberin biosynthesis, except deep Clade III. Hikarchaeia also have nitrile hydratases alongside enzymes for carbon monoxide oxidation and menaquinone biosynthesis, suggesting previously unrecognized roles in nitrogen and carbon cycling. Collectively, our studies reveal niche partitioning of evolutionarily distinct uncultivated Hikarchaeia clades and patterning within the rare biosphere. IMPORTANCE The ocean and its vertical water-column structure are changing with planetary warming; yet, there are many enigmatic microbes, especially those that inhabit the deep ocean. Here, we illuminate a group of uncultivated Archaea that were discovered over two decades ago but still lack clear distributions and habitat preferences. With the first complete hikarchaeal genome now in hand, we identified distinct lineages within the Hikarchaeia that occupy different marine niches. Strong reoccurring seasonal patterns were observed that closely followed the annual cycle of temperature-driven ocean stratification. Given rapid natural and anthropogenic perturbations at hand, establishing baselines for these Archaea is critical for improving our understanding and modeling of marine microbiomes and their biogeochemical functions.
