Molecular Biology and Evolution

Green algae must continuously balance resource availability to maintain photosynthetic performance. The O2:CO2 ratio is a key determinant of their metabolic mode. Under hyperoxia or low CO2, many algae induce a carbon concentrating mechanism (CCM). In the model green alga Chlamydomonas reinhardtii, the CCM relies on a pyrenoid, a specialized microcompartment that elevates CO2 around rubisco. While ambient CO2 acclimation is well-studied, responses to hyperoxia remain poorly understood, despite its frequent occurrence in nature under high light. Using controlled bioreactors, we exposed two diverse Chlamydomonas ecotypes, CC1009 and CC2343, to 95% oxygen to analyze time-dependent, genome-wide transcriptomic and phenotypic changes. Both ecotypes induced CCM genes, but they exhibited distinct molecular and physiological phenotypes. The tolerant ecotype (CC1009) successfully adapted, developing a functional CCM with a structured starch sheath. Conversely, the sensitive ecotype (CC2343) suffered growth arrest and formed malformed pyrenoids. Transcriptomics revealed that CC1009 initiated a rapid initial response, upregulating chloroplast proteostasis and downregulating nucleotide metabolism. CC2343 showed a massive, delayed transcriptional response, downregulating genes coding for photosystems and tetrapyrrole biosynthesis. This unbiased transcriptomic approach identifies key candidate genes driving algal acclimation to hyperoxic stress in natural, high-light environments.

Does the distribution of fitness effects of new mutations vary across the genome? Under the classical Fisher Geometric Model (FGM) we might not expect it to. In FGM, phenotypic traits are envisioned as dimensions of a landscape, with fitness determined by position in the landscape, i.e., the particular combination of traits of an individual. New mutations are represented by vectors that move from an ancestral to a new phenotype. In classical FGM these vectors affect all trait dimensions simultaneously (universal pleiotropy). However, introducing partial and modular pleiotropy into an FGM framework leads to an expectation that parameters of the DFE will vary with mutational pleiotropy-the number of traits affected by individual mutations. Here we address this prediction by investigating whether traits related to mutational pleiotropy, expression level and network connectivity, affect the parameters of the DFE using whole genome data from A. thaliana and C. grandiflora, two closely related Brassica species that vary significantly in their demography and mating system, and therefore, in effective population size and the effects of linked selection. Results were similar across both species. We found that expression level and network connectivity were predictive of the parameters of the deleterious DFE, even once co-correlations among genome biology traits were accounted for. Our results suggest that, across the genome, molecular evolutio(high mutational pleiotropy). nary patterns agree with the predictions of FGM, albeit relaxing the assumption of universal pleiotropy, and that variation in mutational pleiotropy among genes is sufficient to have detectible effects on the DFE. Significance statementHow do the effects of new mutations vary across the genome? If mutations in some genes affect many traits (high mutational pleiotropy), we hypothesise they will be more strongly deleterious, with lower variance in their selective effects. We test this by investigating the distribution of effects of new mutations across genes that vary in features that are related to mutational pleiotropy: expression level, gene network connectivity, and number of associated GO terms. The mean strength and coefficient of variation of selection of new mutations varied across genes with different features in the manner expected by our hypothesis. This demonstrates that important parameters of molecular evolution can vary across the genome with genome architecture.

Plastids house the biology of eukaryotic photosynthesis. The majority of a plastids proteome is imported after cytosolic translation, but a few dozen proteins on average remain organelle-encoded, translated by the plastids own ribosomes. While 1000s of plastid genomes have been sequenced, the availability of less than ten proteomes and only two species with full 70S plastid ribosomal structures limit our understanding of land plant evolution. To address this, we optimized a protocol for the rapid isolation of Marchantia polymorpha chloroplasts that provides a highly enriched and intact organelle fraction from gradient volumes as little as 2 mL. Our approach was successfully applied to six other species, including Chlamydomonas reinhardtii and Nicotiana tabacum. Focusing on M. polymorpha, we determined the proteome of the chloroplast fraction, identifying 1337 nuclear-encoded proteins with a high confidence, where 83% belong to orthologs shared with angiosperms. We further isolated large protein complexes by RNA affinity purification using poly-lysine and provide the high-resolution structures of the 50S subunit of the chloroplast ribosome and RuBisCO from this bryophyte using cryogenic EM and image reconstruction to 2.23 and 2.12 [A] resolution, respectively, highlighting the structural conservation of both complexes. For chloroplasts, our data show that the genome reduction event experienced by the common ancestor of bryophytes has had little impact on the organelles complexity and that they underscore a high level of structural conservation of core components of plastid biology. Our data provide novel resources and methods to explore the functional evolution of plastid proteomes and major macromolecular complexes of cyanobacterial origin.

Developmental competence allows tissues to respond to inductive cues before committing to specialized forms, but how this potential is encoded at clustered gene-family loci is poorly understood. We use vertebrate skin to address this problem. Epidermis responds to regional dermal signals before committing to feather, scale, or differentiated programs, and -keratin loci provide a stringent genomic test: separated type-I/type-II clusters show coordinated transcriptional pairing, yet individual keratin genes are selectively deployed across appendage, differentiation, and disease states. Using chicken developmental genomics with comparative mouse and human epidermal datasets, we show that -keratin clusters are organized before commitment as scaffolded chromatin domains. Within these domains, regulatory elements remain broadly accessible but acquire state-specific activity during commitment and differentiation. Inter-cluster contacts and chromatin-factor perturbation link this architecture to keratin output and morphology. These findings reveal a locus-level chromatin basis for developmental competence, enabling domain-level coordination with gene-level selectivity during epidermal diversification.

Retrons are prokaryotic genetic elements that protect bacterial cells from invading phages. The type IX retron comprises a non-coding RNA, a reverse transcriptase (RT), and dual effectors: a putative HEPN nuclease and a winged helix-turn-helix (WH) protein. Here, we show that the type IX retron system from Klebsiella variicola cleaves host rRNAs and tRNAs upon phage infection, mediating anti-phage defense via an abortive-infection mechanism. Cryo-electron microscopy analysis reveals that the RT, HEPN, and WH proteins, along with multicopy single-stranded DNA (msDNA), form a unique, sheet-like supermolecular complex. Notably, the HEPN active site is encircled by the WH and msDNA within the complex, suppressing the nuclease activity prior to phage infection. A phage-encoded exonuclease cleaves the msDNA, likely releasing the HEPN nuclease to cleave host RNAs and induce growth arrest in infected cells. Overall, these findings highlight the structural and functional diversity of prokaryotic anti-phage defense systems.

Co-transcriptional splicing is a conserved feature of eukaryotic gene expression. However, establishing the functional nature of this process has been difficult. Here using high throughput CRISPR/Cas9 screens we surprisingly find that SF3B3, the third largest subunit of the U2 snRNP complex, is a major regulator of RNA Pol II pause release and processivity. Remarkably, the absence of SF3B3 dramatically perturbs transcription but U2 snRNP assembly and RNA splicing remains unaffected. Mechanistically, SF3B3 coordinates the chromatin occupancy of transcriptional kinases (CDK9/12/13) alongside the PAF1c and Integrator complexes to regulate Pol II. Structure / function analyses of SF3B3 revealed that a metazoan specific 18aa sequence within its disordered tail phenocopies its loss and mediates the physical association and stability of SF3B5. We show that loss of SF3B5 mirrors SF3B3 deficiency suggesting this submodule, although resident within the U2 snRNP complex, evolved to primarily coordinate RNA Pol II in a splicing-independent manner.

Motility of the malaria-causing parasite Plasmodium is essential for transmission to and from mosquitoes, with the turnover of actin filaments being a central feature of productive cell movement. Actin-related proteins (Arps) are known to play critical roles in motility, trafficking and chromatin remodelling. Here, we show that the actin-like protein 1 (Alp1), an apicomplexan Arp, is essential for Plasmodium ookinete motility and establishing of infection in mosquitoes. We identified an insertion region in subdomain 4 that contributes to Alp1 function in ookinetes and show novel actin filament structures in ookinetes. A combination of gene deletion and actin filament recognizing chromobody expression revealed a role of Alp1 in promoting actin filament turnover in ookinetes. We have thus identified a novel Arp that has evolved a specialist function to regulate actin dynamics, govern malaria parasite motility and facilitate malaria transmission.

Symbiotic interactions between plants and nitrogen-fixing microorganisms are essential for sustainable agriculture, yet the molecular mechanisms underlying plant-cyanobacterium symbiosis remain poorly understood. In particular, the nature of the signalling mechanisms mediating partner recognition in associations involving Nostoc species is largely unknown. Recent proteomic analyses have identified proteins homologous to rhizobial Nod factors biosynthetic enzymes in Nostoc punctiforme, suggesting the existence of a Nod-like signalling system. However, the functional role of these components has not been experimentally validated. Here, we investigate the contribution of nod-like biosynthetic and regulatory genes to symbiosis by analysing mutants of N. punctiforme affected in genes with homology to nodB and nodD. Phenotypic characterization revealed that disruption of nodB-like genes does not impair free-living growth but affects early stages of plant association and colonization. Specifically, the nodB1 mutant is impaired in plant association and shows a mild defect in colonization, whereas the nodB3 mutant exhibits a severe defect in colonization. In contrast, nodD-like mutants exhibited altered symbiotic phenotypes, with specific regulators differentially affecting interaction and colonization efficiency in rice (Oryza sativa). In particular, mutation of nodD2 and nodD3 reduced plant association and severely compromised colonization in Oryza sativa, with a more pronounced phenotype in nodD3 mutant. Altogether, our results provide genetic evidence supporting the involvement of Nod-like components in cyanobacterial symbiosis and suggest the existence of a regulatory and biosynthetic module contributing to plant colonization. These findings shed new light on the evolution and diversity of symbiotic signalling mechanisms across plant-microbe interactions.

Differences in physical features and disease prevalence between men and women are examples of sexual dimorphisms. However, sex differences can manifest not only in trait means but also in how strongly risk factors are linked to diseases (e. g. BMI to cardiovascular disease), a question heavily under-researched. To fill this gap, we set out to identify sex differences in phenotype correlations (rP) and decompose them into genetic (rG) and environmental (rE) contributions. Our analysis revealed 250 trait pairs with significant sex-different phenotypic correlations in the UK Biobank. Overall, we observed a predominance of environmental contributions to sex-different effects: 182 trait pairs (73%) exhibited exclusively sex-different rE, while 68 (27%) showed sex differences in both rE and rG, and no trait pair was affected solely by sex-specific rG. For example, we detected sex-different environmental correlation between C-reactive protein and BMI (rE(men) = 0.07 vs rE(women) = 0.25), but no sex-difference in genetic correlation. On the contrary, glycated haemoglobin and LDL cholesterol showed genetic correlation only in women (rG(women) = 0.17; 95% CI = [0.1, 0.23]), but environmental correlation only in men (rE(men) = -0.18; 95% CI = [-0.19, -0.16]). Some of the observed sex differences - including those involving testosterone, SHBG, urate, waist-hip ratio, and triglycerides - may reflect underlying sex-specific genetic architectures, as evidenced by low between-sex genetic correlations. In conclusion, environmental factors are the predominant contributors to sex differences in phenotypic correlations between complex traits, with modest detectable contributions from sex-specific genetic architectures. Recognising these patterns can inform the development of more effective, sex-informed interventions.

Lamina-associated domains (LADs) are large genomic regions that interact with the nuclear lamina (NL). Much of the underlying "grammar" governing their positioning at the nuclear periphery remains unclear. LADs are composed of heterochromatin and typically harbor repressed genes, and their association with the NL is generally incompatible with strong transcriptional activity. The extent to which transcription globally shapes chromatin-NL interactions is not fully understood. Here, we combined acute transcription inhibition using Flavopiridol or Triptolide with genome-wide mapping of chromatin-NL contacts. We found that chromatin-NL interactions are rapidly rewired upon transcription inhibition. Changes in chromatin-NL contacts upon transcription shutdown are predictable based on transcriptional activity and the presence of H3K9me3-marked heterochromatin. This rewiring is reversible, as genome-NL interactions quickly return to baseline levels following drug wash-off. Notably, gain and loss of chromatin-NL interactions upon transcription shutdown reflect two distinct tethering mechanisms. Inter-LADs genomic regions (iLADs) enriched in highly active genes and located near stable LADs, which are tethered by Lamin A (LMNA/C), become re-attached to the NL following transcription inhibition. In parallel, H3K9-methylated regions tethered to the nuclear envelope by the Lamin B receptor (LBR) undergo extensive detachment from the NL. Strikingly, LMNA/C and LBR oppositely regulate transcription-sensitive LADs and are required for transcriptional control of chromatin-NL contacts. Together, our findings highlight the plasticity and dynamic nature of chromatin-NL interactions and provide the first evidence that LMNA/C- and LBR-mediated tethering mechanisms exhibit distinct sensitivities to transcription inhibition. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=155 SRC="FIGDIR/small/738400v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@1c35abborg.highwire.dtl.DTLVardef@79c483org.highwire.dtl.DTLVardef@547ce8org.highwire.dtl.DTLVardef@d4790e_HPS_FORMAT_FIGEXP M_FIG C_FIG HIGHLIGHTSO_LITranscription inhibition alters chromatin-NL contacts rapidly and reversibly C_LIO_LIActive transcription prevents inter-LADs located near LMNA/C-tethered LADs from associating with the nuclear lamina. C_LIO_LILBR-tethered heterochromatin is repositioned away from the NL C_LIO_LITranscription-dependent modulation of chromatin-NL contacts is dependent on LMNA/C and partially on LBR C_LI

As population-scale whole-genome sequencing datasets continue to expand, they enable genetic association studies beyond single-nucleotide variants to more complex forms of genetic variation, including classical human leukocyte antigen (HLA) alleles. The HLA region comprises nine highly polymorphic classical HLA genes in extensive linkage disequilibrium that are associated with numerous autoimmune and infectious diseases. However, unlike genome-wide association studies of single-nucleotide variants, there is no general guidance for controlling the multiple-testing burden in HLA allele association analyses. Here, we systematically evaluated the effective number of independent HLA allele tests using sequencing data from diverse genetic ancestries, analytical derivation and simulations. We show that the multiple-testing burden depends on genetic ancestry, allele frequency, and the phenotype model, but remains remarkably stable across minor allele count thresholds, corresponding to approximately 60-70% of the total number of tested HLA alleles. Simulations further demonstrate that the effective number of tests can exceed 90% under realistic disease models. Analyses of 4-field HLA alleles from long-read sequencing showed that higher typing resolution increases the number of alleles but preserves the underlying correlation structure and scales the effective number of independent tests proportionally. Our results provide practical guidance for HLA association studies and support Bonferroni correction based on the total number of tested HLA alleles as a simple and robust approximation when permutation-based approaches are impractical.

Cells must be primed to rapidly induce inflammatory gene expression upon infection while also tuning the level of induction to avoid immunopathology. Here, we identify RNA polymerase III (Pol III), best known for transcribing noncoding RNAs, as a dual-function regulator of RNA polymerase II (Pol II)-dependent inflammatory gene expression. Pol III is selectively enriched at promoters of innate immune, pro-inflammatory, and stress-response genes, where it maintains chromatin accessibility and supports basal transcription. Upon infection with murine gammaher-pesvirus 68 (MHV68), Pol III redistributes from these promoters to retrotransposon loci, coinciding with enhanced expression of inflammatory genes. Depletion of the Pol III transcription factor Brf1 further amplifies inflammatory transcription during infection with MHV68, herpes simplex virus-1, and influenza A virus. Genes restrained by Pol III have TATA-box-enriched promoters and are functionally dependent on TATA-binding protein (TBP), suggesting that Pol III modulates inflammatory gene expression by competing with Pol II for shared transcriptional machinery. Thus, Pol III is a chromatin licensor in uninfected cells and an inflammation rheostat during viral infection. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=178 SRC="FIGDIR/small/738346v1_ufig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@d99325org.highwire.dtl.DTLVardef@4b781dorg.highwire.dtl.DTLVardef@bad1b6org.highwire.dtl.DTLVardef@11e41a6_HPS_FORMAT_FIGEXP M_FIG C_FIG

Topoisomerase II (TOP2) resolves DNA topological constraints through a tightly regulated cycle of DNA double-strand cleavage and religation. Nearby DNA damage or chemotherapeutic agents such as etoposide block the DNA religation step, stabilizing TOP2-DNA cleavage complexes (TOP2ccs) at DNA double-strand breaks (DSBs). The SUMO E3 ligase ZATT (ZNF451) has recently emerged as a key effector of TOP2cc repair, but its mechanism of action remains poorly understood. Here, we show that ZATT is sufficient to resolve TOP2ccs independently of TDP2, TOP2 proteolysis, and canonical DSB repair pathways. Using Xenopus egg extracts and biochemical reconstitution, we find that ZATT salvages trapped TOP2 by promoting TOP2 release from its stalled cleavage complex. Structural modeling and targeted mutagenesis in Xenopus egg extracts and human cells identify a highly conserved hydrophobic pocket in the tower domain of TOP2 where the ZATT coiled-coil "hooks on" to promote TOP2cc resolution. Our findings reveal a new strategy to resolve TOP2ccs that bypasses the exposure of dangerous DNA breaks.

Antimicrobial resistance (AMR) is an ever-increasing threat to population health. Industrial, environmental and societal factors are increasingly recognized as important contributors to AMR within communities. Here, we investigated the spatial distribution of AMR genes (ARGs) across Alberta, Canada and their association with socio-economic, immigration-related, and agro-industrial characteristics using municipal wastewater-based surveillance. We analyzed monthly wastewater metagenomes collected between March 2022 and March 2023 across eleven municipalities, representing 39% of Alberta's population. Integration with census data enabled multivariate analysis, revealing that municipal resistome profiles were strongly structured along income and immigration-related population gradients. ARGs spanning 14 resistance classes exhibited distinct distributional patterns across income and immigration gradients, including contrasting associations among beta-lactam, aminoglycoside, and macrolide-lincosamide-streptogramin ARGs, consistent with heterogeneous selection pressures across sub-populations. These findings demonstrate the capacity of longitudinal wastewater surveillance to identify persistent population-level resistome patterns and highlight the importance of incorporating sociodemographic context into AMR surveillance and mitigation strategies.

Various methods have detected miRNA-target interactions via immunoprecipitation of UV-crosslinked Argonaute ribonucleoprotein complexes, followed by intermolecular ligation of bound miRNAs to target strands, forming chimeric RNAs. To date, these methods have relied on conventional viral reverse transcriptases (RTs) to generate cDNAs for sequencing. However, crosslinked RNAs often retain adducts after purification, which can make them poor templates for viral RTs. Here, we adapted OTTR (Ordered Two-Template Relay) techniques to generate cDNAs from Ago2-bound RNAs. OTTR makes use of a modified retroelement-encoded RT, which is strongly processive even on templates with modifications or adducts. We show that this "OTTR-CLASH" method increases the frequency of generating chimeric RNAs compared to previous methods. We also developed an improved bioinformatic pipeline for analysis of these data, and we use this to catalog miRNA-target interactions not previously described in the literature. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=147 HEIGHT=200 SRC="FIGDIR/small/738487v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@13bc276org.highwire.dtl.DTLVardef@5beb41org.highwire.dtl.DTLVardef@b204e5org.highwire.dtl.DTLVardef@15f747d_HPS_FORMAT_FIGEXP M_FIG C_FIG

An epidemic's expected course is determined by the magnitude and timing of a typical person's infectiousness --- captured, in turn, by the basic reproduction number and the generation-time distribution. These fundamental, population-average quantities can mask individual-level variation that shapes how an epidemic actually unfolds: for example, individual variation in the magnitude of infectiousness (overdispersion) creates superspreading, a key feature of the SARS-CoV-1 and SARS-CoV-2 epidemics. However, the impact of individual variation in infectiousness timing is less well understood. Here, we demonstrate that individual infectiousness timing varies substantially and to different degrees across pathogens. For some common pathogens, including influenza, measles, and SARS-CoV-2, infectiousness is "bursty", or highly concentrated and variably-timed across individuals: for example, the window of appreciable infectiousness for SARS-CoV-2 may last for roughly a day, vs. the 9--12 days usually quoted. We show that bursty infectiousness creates superspreading without inherent superspreaders, makes epidemic timing more variable, amplifies the time-sensitivity of common interventions, and complicates inference of key epidemiological parameters. Together with the reproduction number, the generation-time distribution, and overdispersion, burstiness completes a family of basic parameters that govern how epidemics unfold.

Background Coccidioidomycosis is an emerging fungal disease across the arid Americas and a frequent cause of community-acquired pneumonia. Understanding where Coccidioides populations originate, how they move across space, and whether they are expanding is important for interpreting changing patterns of Valley fever and anticipating future infection risk. Methods We prospectively collected and whole-genome sequenced 186 Coccidioides-positive clinical isolates submitted to a national diagnostic laboratory, and included 126 previously sequenced genomes. We applied genomic clustering, time-calibrated phylogenetic reconstruction, ancestral area reconstruction, mating-type assignment, and demographic inference to identify major populations, infer dispersal patterns, assess evidence for recombination and clonality, and reconstruct historical population dynamics. Findings We analyzed 312 genomes (139 C. immitis; 173 C. posadasii) and identified three major genetic populations within each species. C. immitis included two California-centered populations and one Pacific Northwest population, whereas C. posadasii included two Arizona-centered populations and one Texas-centered population. The most recent common ancestor was estimated at approximately 127,000 years for C. immitis and 234,000 years for C. posadasii. Most populations were not fully monophyletic, consistent with retained ancestral variation and/or ongoing gene flow. Inferred dispersal was largely asymmetric, with most movement originating from California in C. immitis and from Arizona and Texas in C. posadasii. Most populations contained both mating types, but one C. immitis population and a Brazilian subgroup of C. posadasii were clonal. All populations showed recent demographic expansion. Interpretation The evolutionary history of Coccidioides is characterized by strong geographic structure, ongoing gene flow, and recent demographic expansion. These processes are likely to influence future patterns of Valley fever endemicity and supports the use of genomic surveillance to detect shifts in disease risk as environmental conditions change.

West Nile virus (WNV) has become an important public health concern in Europe. Italy is one of the most affected countries, yet our understanding of WNV epidemiology, genomics, and dispersal across hosts and geographic regions is incomplete. AIM: To reveal the history of WNV in Italy by integrating epidemiological, genomic, and environmental data into descriptive and quantitative assessments of its past spatio-temporal surveillance and expansion. We collated vertebrate and mosquito WNV records from national surveillance and the scientific literature spanning multiple decades. Historical serological and molecular data were summarized by host and region, climatic associations with case trends were assessed using regression models, and phylodynamic and phylogeographic analyses reconstructed viral introductions and dispersal within Italy.WNV circulation in Italy has changed markedly over time, with increasing human case reporting and expansion beyond historically affected northern regions. Climate-informed regression models explained recent reporting trends, supporting an environmental contribution to transmission. Phylodynamic analyses identified multiple independent introductions and sustained local transmission with increasing regional connectivity. Wavefront analyses revealed lineage-specific dispersal patterns associated with seasonal climatic gradients. Discrepancies between epidemiological records and genomic sampling highlighted uneven surveillance across regions and host species.WNV emergence in Italy reflects repeated viral introductions, local persistence, heterogeneous surveillance, and environmentally associated dispersal dynamics. Strengthening integrated surveillance combining epidemiological, environmental, and genomic data will improve early detection, the monitoring of transmission dynamics, and public health preparedness under ongoing environmental change.

The Ser/Thr kinase ATM orchestrates cellular responses to DNA double-strand breaks (DSBs) and promotes DSB repair by homologous recombination. In this process, ATM is activated by DNA and the MRN (MRE11, RAD50, and NBS1) complex. Here we show that mutations of the conserved PIKK regulatory domain (PRD) within ATMs kinase domain can confer a maximally active state that no longer requires MRN/DNA. In ATM-knockout human cells, the PRD mutants display substantially higher phosphorylation of histone H2AX, KAP1, and CHK2 than wild-type ATM, with or without IR-induced DNA damage. Cryo-EM structures of two PRD mutants each revealed basal or activated conformations depending on bound ligands, suggesting that disrupting the ordered portion of the PRD results in an enzyme poised to transition to the active conformation. However, the identity of the active-site nucleotide is a key driver of the conformational switching. We speculate that this plasticity might be exploited to develop small-molecule ATM modulators for therapeutic applications.

Malaria subnational tailoring is often a population-level allocation problem: which interventions should be prioritized, at what coverage, and under what budget and uncertainty assumptions? We present DELENDA, a differentiable compartmental model of Plasmodium falciparum transmission designed for posterior calibration and intervention-mix optimization. We fit a NUTS posterior jointly to age-stratified prevalence and clinical-incidence data from five sub-Saharan African sites plus three pre-intervention Garki Project villages, spanning a broad entomological inoculation rate (EIR) range. DELENDA is implemented in JAX, which makes the full simulation differentiable. This enables efficient Bayesian inference and continuous constrained optimization over intervention coverage. We apply the framework to an illustrative decision problem: a highly seasonal transmission setting where coverage is optimized for ITNs, SMC, IRS, and pediatric malaria vaccination across EIR, budget, objective, and uncertainty grids. Three findings are decision-relevant. First, intervention rankings are more robust than projected impact: posterior, vector-biology, and intervention-efficacy uncertainty change optimized coverage modestly but substantially widen the distribution of cases averted. Second, the objective matters: under-five optimization brings child-targeted SMC and vaccination in earlier, whereas all-age optimization delays vaccination and favors broader population protection through IRS. Third, cost uncertainty is mainly a constraint-side problem: expected-cost optima have material budget-overrun probability, while tail-risk budget rules sharply reduce overrun risk at the cost of lower effective coverage and fewer expected cases averted. DELENDA therefore demonstrates an uncertainty-first approach to subnational tailoring: differentiable model structure exposes the biological parameter space to posterior calibration and carries biological and operational uncertainty into constrained decision optimization, tasks that are difficult with the non-differentiable models currently central to SNT workflows.