mLife

We developed a convolutional neural network-based machine learning technique to simultaneously analyze the morphology and motility of spirochetal bacteria swimming with continuous cellular deformation. Matching probabilities between experimental images and learned models realizes quantification of cell morphology and association with motility. This method can be applied to diverse transformable cells, offering critical biophysical insights into microbial dynamics.

Biological ethanol production is important for the circular carbon economy and makes up 73% of the U.S. biological fuels market. Previously, we produced ethanol by reversing methanogenesis and capturing methane by cloning methyl-coenzyme M reductase (Mcr) from an unculturable population of anaerobic methanotrophic archaea; this process was predicated on the generation of the intermediate acetate and its conversion by the methanogenic host to ethanol. Moreover, methanogens are generally thought to be detrimental for converting acetate to ethanol and are usually intentionally inhibited. Here, we demonstrate that direct growth on acetate as the sole carbon and energy source by the methanogen Methanosarcina acetivorans C2A results in 40% of the metabolized acetate becoming ethanol and that there is 430% more ethanol produced, compared to growth on methane via Mcr. In addition, we found growth on methanol results primarily in methane generation and low levels of ethanol. Therefore, acetate may be readily converted by the methanogen M. acetivorans to ethanol at high yields.

The basidiomycete Ustilago maydis is a well-characterized model organism for studying pathogen-host interactions and of great interest for a broad spectrum of biotechnological applications. We set here to develop light inducible molecular tools to enable dynamic studies on signaling networks and fungi-host communication, and for metabolic engineering approaches. In particular, light-controlled, optogenetic switches provide quantitative, spatio-temporal control capabilities, are minimal invasive and reversible. We engineered two blue light-inducible LOV-domain-based gene expression switches, to up- (Blue-ON) and down-regulate (Blue-OFF) gene expression, and performed a functional characterization in sporidia and hyphae of U. maydis. Profiting from the dynamic control ranges and rapid kinetics, we implemented the optoswitches to control cell morphology by initiating the transition from a haploid sporidial cellular morphotype to filaments upon regulation of the levels of the polarity factor Rac1 and its constitutive active mutant Q61L. In addition to showing how expression level of effectors can be precisely regulated as an approach to understand fungi-plants interaction, we show in two proof-of-principle applications targeted control over U. maydis filamentous fungal invasion of plant tissue and the mechanisms of tumor formation. For this we placed under Blue-ON and Blue-OFF control two U. maydis effectors, See1 (Seedling efficient effector 1) and TIN2 (Tumor inducing 2), and tumor formation was assayed on maize leaves. Taken together, this study established blue-light switches as effective tools to control morphogenesis and pathogenesis in U. maydis.

Most proteins targeted to the organelles of endosymbiotic origin are encoded in the nuclear genome, placing them under the regulatory dominance of the nucleus. For photosynthetic eukaryotes, nuclear-encoded chloroplast proteins arise via two routes: First, genes of cyanobacterial origin were relocated to the nucleus through endosymbiotic gene transfer (EGT). Second, proteins of eukaryotic origin emerged to support chloroplast function and structure. These proteins are reimported into the chloroplast via an import machinery. Reversing the transfer of such genes from the nucleus to the chloroplast genome may offer insights into chloroplast regulation and evolution. In this study, we established a highly efficient and accessible electroporation protocol for chloroplast transformation in the green alga Chlamydomonas reinhardtii, and used it to reverse-transfer two nuclear-encoded genes encoding proteins arising via the two routes described above: the cyanobacteria-derived chloroplast division protein FtsZ1 and the Rubisco-linker EPYC1 of eukaryotic origin. Regardless of origin, both chloroplast-encoded FtsZ1 and EPYC1 showed proper localization and functionality comparable to their nuclear-encoded counterparts. Together, our study provides a robust protocol for chloroplast transformation, a platform for investigating the evolutionary drivers of EGT, and a foundation for advancing chloroplast bioengineering. SIGNIFICANCE STATEMENTO_LIEndosymbiotic gene transfer has resulted in the mass migration of genes from the chloroplast genome to the nuclear genome. Reversing the gene transfer could reveal the evolutionary significance of genome partitioning. C_LIO_LIUsing the green alga Chlamydomonas reinhardtii, this study developed an efficient, electroporation-based protocol for chloroplast transformation. Relocating the genes encoding two chloroplast-targeted proteins, FTSZ1 and EPYC1, to the chloroplast genome showed that the proteins maintained normal localization and function. C_LIO_LIThe established transformation protocol facilitates systematic testing of reverse gene transfer to elucidate the potential evolutionary advantages of genome partitioning and opens new avenues for chloroplast bioengineering. C_LI

Multidrug-resistant pathogens pose a major threat to One Health. Within the past decade, CRISPR-Cas systems have been explored as sequence-specific antimicrobials. While chromosomal injury has been considered the primary mechanism underlying pathogen killing by CRISPR-Cas antimicrobials, the synergistic role of gene disruption together with chromosomal injuries remains poorly understood. In this study, we characterized a new class of CRISPR-Cas antimicrobials that simultaneously cotarget essential and defensive genes to enhance potency against the clinically relevant pathogen Staphylococcus aureus. High-throughput CRISPR screening identified top-performing guide RNAs for twenty functionally diverse essential and defensive genes across the S. aureus genome. CRISPR-Cas antimicrobials were modularly formulated to target single or multiple gene loci and packaged in phage-like particles for specific delivery. By engineering an S. aureus production host with a chromosomally integrated anti-CRISPR protein, we demonstrated efficient production of CRISPR-Cas antimicrobials targeting any S. aureus chromosomal locus without self-targeting. Characterization of CRISPR-Cas antimicrobials with single guide RNA designs revealed that potency varied according to targeted gene function, achieving up to a 4-log10 reduction in viability and outperforming traditional antibiotics. Multiplexed configurations were consistently more effective than single-targeting designs, with the top-performing design demonstrating a 4.7-log10 reduction in viability. Cotargeting essential and defensive genes revealed synergies that led to improved lethality and attenuated resistance, with enhanced activity in biofilms compared to traditional antibiotics. Genes involved in signaling and stress responses were important defensive targets for developing cotargeting CRISPR-Cas antimicrobials. Overall, this study establishes design principles for synergistic CRISPR-Cas antimicrobials applicable to next-generation precision antimicrobial development. SIGNIFICANCEThe ability to effectively combat multidrug-resistant pathogens is of primary importance to One Health. This study develops a generalizable design principle for formulating potent CRISPR-Cas antimicrobials that exploit synergistic cotargeting strategies for enhanced pathogen killing. In addition to chromosomal injuries, we found that disruption of gene function plays a crucial role in determining the lethality of CRISPR-Cas antimicrobials, providing a generalizable framework for effective CRISPR-Cas antimicrobial design. The development of a CRISPR-Cas antimicrobial production host with stable, chromosomally integrated anti-CRISPR genes greatly expands the modularity, adaptability, and efficiency of formulating CRISPR-Cas antimicrobials and enables deeper insights into the molecular mechanisms involved in eliminating multidrug-resistant pathogens.

The discovery of sensory ion channels, such as thermosensitive transient receptor potential (TRP) channels and mechanosensitive PIEZOs, have transformed our understanding of mammalian sensory biology. However, the sensory receptor landscape remains incomplete, as many physiologically relevant sensory stimuli still lack identified molecular targets. Here, we describe a novel screening strategy utilizing FM 1-43, a fluorescent marker for activity of various cation channels, with a CRISPRa library (MPCL) targeting multi-transmembrane domain proteins. We validate this method by focusing on allyl isothiocyanate (AITC) and its putative receptor TRPA1. Specifically, we show that CRISPRa-mediated overexpression of TRPA1 is sufficient for FM 1-43 labeling when co-treated with AITC. Furthermore, we show that using FM 1-43 and AITC, we can efficiently FACS enrich TRPA1-expressing cells from a pool of MPCL-expressing cells. Collectively, this presents a novel method for rapidly screening select cation-dependent sensory stimuli.

Root-associated microorganisms play a pivotal role in helping plants adapt to drought stress. However, the underlying mechanisms of the rhizospheric microbiome under limiting soil moisture remain largely unresolved. Integrating total and active microbiome analyses enables a more accurate interpretation of microbial responses to climate change-associated water stress. We assessed the effect of reduced rainfall on two wheat genotypes, drought-tolerant (DT) and drought-sensitive (DS), using rainout shelters that allowed 100%, 75%, 50%, and 25% of natural precipitation to reach the crop. At the peak of the growing season, rhizosphere samples were collected for metagenomic (MG) and metatranscriptome (MT) sequencing. In parallel, rhizosphere volatile organic compounds (VOCs) were collected and analysed. Differential expression analysis of metatranscriptomic data using metagenomic abundance as a cofactor was performed by comparing all treatments to the 100% precipitation control. Our results demonstrate that particularly oxidative stress-related transcripts intensify in DS as rainfall decreases. Transcriptomic shifts primarily involved upregulation of transcripts associated with antioxidant (catalase, superoxide dismutase), heat shock proteins (Hsp10, Hsp60, DnaK/DnaJ, GroEL, GroES), as well as microbial functions related to osmoregulation, proline and glycine betaine (PutA, PutP, OpuBB), and plant growth-promoting traits such as auxin production, phosphate solubilization. Moreover, volatile organic compound (VOC) emissions differed significantly between the control and drought treatments, with higher emissions, particularly acetates, in the DS genotype than in the DT genotype. Overall, pronounced drought-induced shifts in active microbial functions and VOC emissions indicate high sensitivity and functional plasticity of the active microbiome, whereas the total microbiome remains robust under medium drought.

Premise: Rapid and accurate plant species identification is a critical challenge exacerbated by the taxonomic impediment. Although portable near-infrared (Micro NIR) spectroscopy represents a promising solution, the current absence of standardized protocols and a fundamental understanding of how critical acquisition and analysis parameters influence accuracy remain significant barriers. This study focused on the systematic optimization and validation of a comprehensive workflow designed to maximize the reliability of plant identification using this technology. To ensure methodological robustness across diverse foliar matrices, four vascular plant species were strategically selected as a representative test set to encompass morphological extremes, including significant variations in leaf thickness, pubescence, and surface texture. Methods: Using a portable spectrometer on herbarium specimens (exsiccate) of four vascular plant species, we systematically tested five spectral backgrounds, seven pre-processing methods, and four classification models. Subsequently, we optimized the number of spectral readings and evaluated the influence of the leaf scanning surface (adaxial vs. abaxial) on model accuracy. Results: The highest-performing combination was a Shiny Aluminum background, Second Derivative pre-processing, and a Random Forest model, which achieved a mean cross-validated accuracy of 99%. An average of just three spectral readings from the adaxial (upper) leaf face was sufficient to saturate model performance, proving statistically superior to other approaches (p < 0.001). Discussion: This study establishes a validated, high-accuracy protocol for plant species identification from herbarium specimens using portable NIR, offering a powerful tool for biodiversity studies. Direct applicability to fresh plants in the field requires future validation to account for the spectral influence of moisture variability.

Culture conditions were optimized for the production of melanin nanoparticle by the bacterial strain Pseudomonas stutzeri BTCZ 305. Response surface methodology was employed for determining the most significant fermentation conditions using variables including, pH, temperature and L-tyrosine concentration identified through one-factor-at-a time approach. Box-behnken design consisting of 17 different combinations of all these factors were performed. Using this methodology, a quadratic regression model was built and the optimal combinations of media constituents for maximum melanin production 1192.27 microg/mL were determined as temperature (32.5 degreeC), pH (8.5) and L-tyrosine concentration (7 g/L). Melanin production was obtained experimentally coincident with the predicted value and the model was proven to be adequate. The nanostructural distribution, its stability in colloidal suspension and particle size were also characterized with the help of TEM, particle size analysis and Zeta potential. The potent applicability of this molecule in anti-inflammation and wound healing was also elucidated.

Nutrient-rich food-processing wastewaters represent valuable yet under-utilised side streams for sustainable protein production in the form of microbial biomass. Here we present an integrated dual-loop bioprocess that converts soybean-processing wastewater into microbial single-cell protein (SCP) while achieving substantial nutrient removal and product refinement. In the first loop, previously enriched microbial consortia were inoculated and cultivated in four parallel sequencing batch reactors (SBRs) for 44days at a hydraulic retention time (HRT) of 3days. This bioprocess configuration demonstrated features that support future scale-up while maintaining process stability, achieving a protein content of 33.3{+/-}3.2%, doubling the protein yield (15.32{+/-}3.49g dry weight per g soluble TKN) and quadrupling the production rate (0.29{+/-}0.06g dry weight L-1 d-1) compared to operating reactors without inoculation (HRT: 7.2days). Effluent treatment was stable, with 84% carbon and 78% nitrogen removal efficiencies, demonstrating efficient nutrient recovery. The SCP biomass was enriched in functional taxa, including Acidipropionibacterium, Lactococcus, Megasphaera, and Azospirillum, suggesting that reactor conditions and inoculum selection promoted a stable, protein-productive microbial community with potential probiotic benefits. In the second loop, bioreactor effluent was reused as aqueous matrix for heat treatment (60{degrees}C) of the SCP biomass, reducing the RNA content from 8.6% to 2.6%, with a 39% biomass loss accompanied by a 30% increase in total amino acid concentration. Hence, our valorisation approach integrates microbial biomass production, effluent reuse, and product refinement within a circular framework. The system provides a resource-efficient pathway for converting food-sector side streams into high-quality microbial community-based SCP, highlighting its potential scalability for sustainable nutrient and water management.

Microbial fuel cells (MFCs) technology offers sustainable electricity production. Current research largely focuses on few select model organisms, therefore the true prevalence of exoelectrogenesis amongst bacteria remaining largely unknown. We present a broad-scale survey of monomicrobial electricity production among environmental bacterial isolates inoculated in MFCs, using model organism Shewanella oneidensis MR-1 as a benchmark. Of the assessed taxa, 11-22% displayed exoelectrogenic activity, exceeding current predictions and identifying a further three novel exoelectrogenic species. Phylogenetic analysis based on the 16S sequences enabled the evolutionary relationship between isolates to be visualised, revealing that exoelectrogenesis is non-randomly distributed and phylogenetically conserved. Polarisation studies were implemented, revealing that numerous electron transfer mechanism were being utilised to perform exoelectrogenesis. The results of this study imply that bacterial electricity production is more widespread amongst culturable bacteria than previously estimated, with implications for bioprospecting novel exoelectrogens and predicting electrogenic activity in diverse microbial communities.

BackgroundMethyltransferase-like 1 (METTL1) is highly expressed in organs like the pancreas but less so in the brain. The METTL1-WDR4 complex catalyzes N7-methylguanosine (m7G) methylation in tRNA, miRNA, mRNA, and rRNA, which impacts RNA stability and function. These modifications affect mRNA translation and tRNA functionality, influencing protein production and cellular activities. Such modifications can regulate tumor growth, invasion, and metabolism by selectively controlling protein expression. MethodGene expression data from public databases were analyzed to compare METTL1 expression in normal and tumor tissues. Western blot (WB) and immunohistochemistry (IHC) were used to quantify METTL1 levels in glioma samples and assess their prognostic significance. Cell viability, migration, invasion, and proliferation were evaluated using Cell Counting Kit-8 (CCK-8), wound healing, Transwell, cell cycle analysis, and colony formation assays. RNA immunoprecipitation PCR (RIP-PCR) identified m7G methylation sites on EPHA2 mRNA, and RNA stability was assessed with actinomycin D. ResultsBioinformatics analysis revealed that METTL1 is overexpressed in gliomas, correlating with poor prognosis. Knockdown of METTL1 significantly affected cell proliferation, migration, and invasion. RNA sequencing (RNA-seq) and m7G analysis identified EPHA2 as a downstream target, influencing the cell cycle via the AKT pathway. RIP and methylated RNA immunoprecipitation (MeRIP) confirmed two m7G sites on EPHA2 mRNA regulated by METTL1. Small interfering RNA (siRNA)-mediated METTL1 knockdown in EPHA2 mutants affected mRNA stability. Rescue experiments restored cell proliferation and AKT pathway gene expression. ConclusionMETTL1 methylates EPHA2 mRNA, enhancing its stability and expression, which activates the AKT signaling pathway and influences glioma cell proliferation. METTL1 could be a potential therapeutic target in glioma treatment.

Melanins are biological macromolecule with immense functionality synthesised by a wide spectrum of living organism. It is mainly synthesised by the oxidative polymerization of indolic and phenolic compounds through several enzymatic process. It has wide spread application in agriculture, cosmetic and therapeutic industry due to its various properties including antioxidation ability, UV protection efficiency and anticancer activity. Because of this wide range of application in different sectors, large scale production and commercialization attains enormous consideration. The present study deals with the effect of 12 different process parameters on melanin production viz., production media, incubation time, inoculum concentration, pH, temperature, agitation, carbon source, phosphate and magnesium source, CuSO4.5H2O, sodium chloride and L-tyrosine on melanin production by Pseudomonas stutzeri strain BTCZ 109 obtained from Arabian sea sediments was evaluated. After optimizing the important process parameters, the bacteria showed about ~4.65 fold increase in melanin production compared to unoptimized cultural conditions. The melanin optimized through this method was found to be nano sized. The Nano sized DOPA melanin in treating Skin cancer cell line SK ML28 which showed a dose-dependent activity with an IC50 value of 164 g/mL. All these results highlight the therapeutic efficiency of DOPA melanin Nano particle as promising bioactive molecule.

Cytoskeletal plasticity is a defining feature of cancer progression, enabling tumor cells to adapt their morphology, mechanics, and migratory behavior during invasion and metastasis. Although actin filaments, microtubules, and intermediate filaments are known to cooperate in these processes, the molecular mechanisms coordinating their dynamics remain incompletely understood, particularly the role of post-translational modifications (PTMs). Here, we developed CytoFRET2, a multiparametric cytometry-based FRET platform that enables real-time and simultaneous monitoring of the dynamics of actin filaments, microtubules, and vimentin in living suspension cells. The system combines fluorescently tagged cytoskeletal reporters with spectral flow cytometry, allowing simultaneous high-content analysis of multiple cytoskeletal networks while overcoming autofluorescence and fluorescence interference from small molecules. Using spectral CytoFRET2, we screened a small library of epigenetic compounds targeting regulators of acetylation and methylation pathways. The screen revealed that inhibition of lysine deacetylases (KDACs) and sirtuins promoted stabilization of both microtubules and vimentin filaments, without impacting actin filament organization. In contrast, inhibition of lysine acetyltransferases (KATs), particularly with garcinol and anacardic acid, induced rapid vimentin disassembly. Mechanistically, the study reveals acetylation as a key post-translational modification regulating the dynamics of microtubules and vimentin filaments, with KAT inhibitors emerging as potent modulators of vimentin organization. Together, the findings establish spectral CytoFRET2 as a versatile platform for systematic investigation of cytoskeletal regulatory networks and therapeutic vulnerabilities in cancer.

Background: Biochemical, biophysical and structural characterisation of isozymes from the ubiquitous family of iron- or manganese-dependent superoxide dismutases (SodFMs) requires the purification of high-quality preparations of recombinant enzymes. Determination of their key biochemical parameter, their catalytic metal-preference, requires the comparison of the catalytic turnover of samples loaded exclusively with iron versus samples loaded exclusively with manganese. Both of these aims are inhibited by the potential contamination of recombinant preparations of SodFMs, prepared by heterologous overexpression inside Escherichia coli cells, by even low levels of endogenous SodFMs from the host, both of which show very high turnover with either manganese (E. coli MnSOD) or iron (FeSOD). To overcome this problem, we created a strain of E. coli lacking the endogenous SodFMs. Here, we characterised this E. coli BL21 (DE3) {Delta}sodA{Delta}sodB strain, determining the physiological effects of SodFM deletion and demonstrating its utility for producing recombinant SodFMs for in vitro characterisation and use. Results: Genomic analysis verified the targeted gene deletions, without off-target effects. Growth, expression, elemental analysis, and proteomic data confirmed a lack of physiological defects of the strain except for a known inability to grow on glucose, which is overcome by heterologous SodFM expression. We demonstrate the utility of the strain for the efficient production of diverse recombinant SodFMs, including highly divergent, understudied isozymes, including the ability to precisely control the metal-loading of the heterologously expressed protein. Conclusions: The E. coli strain described herein is a useful microbial cell factory for production of recombinant SodFMs, which should find widespread utility as expression host of choice, enabling more efficient production of protein for studies of the biochemical, biophysical and structural properties of this remarkable family of metalloenzymes.

Cysteine and serine proteases act as an immune hub in the plant apoplast to provide robust extracellular immunity during microbial colonisation. Microbial pathogens counteract these immune proteases by inhibiting their activity using small secreted proteins (SSPs). Traditionally, SSPs with protease-inhibitory activity are predicted using sequence-dependent database searches. However, in recent years, fungal SSPs have been shown to exhibit protease-inhibitory functions despite lacking the inhibitor domain that is annotated through sequence similarity searches. Hence, a large number of these novel SSPs with putative protease inhibitor functions are missed during detection and filtered out during sequence similarity searches. This necessitates the development of newer approaches to predict SSPs lacking an annotated inhibitor domain. Machine learning approaches, such as protein language models, have emerged as powerful tools for predicting protein functions. To date, no machine learning models have been developed to predict the protease-inhibitory activities of SSPs lacking an annotated inhibitor domain. Here, we introduce a protease inhibitor prediction pipeline, PINPOINT (Protease INhibitor PredictiOn at plant-pathogen INTerface). The PINPOINT pipeline combines fine-tuned protein language model classifiers, a structure-aware autoencoder, and effector prediction into a multi-level framework for identifying SSPs with predicted protease inhibitor functions. PINPOINT predicts protease inhibitors using SSPs sequences and monomeric structures with pre-computed structures obtained from the AlphaFold Protein Structure Database or predicted using the ESMFold public API. We successfully validated the PINPOINT platform using SSPs from the plant fungal pathogen Macrophomina phaseolina. Notably, the PINPOINT platform robustly predicted several of these SSPs as protease inhibitors including Sequence-unrelated but structurally similar (SUSS) effectors. We further validated the inhibitory potential of these predicted M. phaseolina SSPs using AlphaFold Multimer (AFM) screening against candidate apoplastic soybean cysteine and serine proteases. Additionally, this platform can be used as a pre-filtering step in AFM screening approaches to reduce the number of candidates for discovering novel SSPs with protease inhibitor function for cross-kingdom plant-microbe interaction studies. The PINPOINT platform will accelerate the prediction of novel SSPs including SUSS effectors with protease inhibitor functions in proteomes of any organisms. We made the PINPOINT pipeline accessible to the research community as a web-based notebook environment for interactive computing in Google Colab, available at https://github.com/iitj-mpg-lab/PINPOINT

Natural products are central mediators of microbial interactions. However, once released into the environment, they also become available for neighboring microorganisms capable of degrading and modifying them through biotransformation. These biotransformations may fundamentally reshape metabolomes and influence community behavior, yet our understanding of these processes remains limited. Ribosomally synthesized peptides are particularly compelling in this context because their structural complexity and potent antimicrobial activity coexist with the potential to yield essential nutrients and reduced bioactivity through biotransformation. Identifying the pathways underlying these biotransformations is essential for understanding mechanisms that support microbial coexistence and nutrient recycling in soil microbiomes. Here, we used nisin as a model peptide to investigate biotransformation by soil bacteria. Selective isolation under nisin-rich, carbon-limited conditions yielded two Gram-negative isolates, Burkholderia stabilis and Pseudomonas fragi. Using growth assays and liquid chromatography-mass spectrometry, we found that both isolates grow in the presence of nisin while biotransforming and depleting the peptide. Burkholderia stabilis completely converted nisin through sequential cleavage of the C-terminus, hinge region and lanthionine ring C, whereas Pseudomonas fragi showed more limited processing restricted to the C-terminal region. Although these biotransformations dismantled structural features required for nisins antimicrobial activity, the intrinsic resistance of both isolates suggests a role beyond detoxification. We further detected nisin biosynthetic genes in the source environment, supporting nisins ecological relevance and suggesting that these bacteria may participate in its turnover in soil. Together, these findings reveal extensive microbial processing of nisin and support a role for antimicrobial peptide recycling in soil microbiomes.

Primary production in the Southern Ocean (SO) plays a critical role in regulating the global carbon cycle, yet the physiological mechanisms governing phytoplankton responses to iron (Fe) limitation and variable light remain poorly constrained. Using a custom made incubation system that simulated natural diel solar variability, we examined the interactive effects of Fe availability, light intensity, and photoperiod (continuous vs. variable) on three ecologically important SO phytoplankton: Fragilariopsis cylindrus, Phaeocystis antarctica, and Thalassiosira antarctica. Physiological, photophysiological, and proteomic measurements revealed that Fe availability was the dominant factor regulating growth, carbon production, photosynthetic performance and protein expression across all species. Distinct acclimation strategies emerged: F. cylindrus exhibited marked trade-offs between productivity and photoprotection under Fe stress, consistent with adaptation to stable, low-light, Fe-poor environments; P. antarctica maintained growth by flexibly modulating photoprotective and photosynthetic capacity, reflecting high plasticity suited to dynamic, open-ocean conditions; and T. antarctica expressed a balanced strategy, sustaining productivity and photoprotection simultaneously, characteristic of coastal bloom formers with higher Fe demand. Dynamic light regimes produced smaller, species-specific effects, influencing chlorophyll content and carbon storage primarily in T. antarctica. Correlation and z-score analyses demonstrated that Fe-rich photosynthetic proteins co-varied with biomass production, whereas photoprotective traits clustered independently, underscoring divergent energy-allocation strategies. Together, these results reveal how SO phytoplankton partition resources between productivity and photoprotection under shifting Fe-light regimes, providing mechanistic insight into their ecological niches.

Transposon mutagenesis is a powerful method to create deep libraries of genetically diverse cells. However, it has previously not been possible to analyze transposon libraries with respect to complex phenotypes as characterized by intracellular spatial dynamics. Here, we use optical pooled screening to characterize a transposon mutagenesis library via live cell single-particle imaging. The library is analyzed in real time, which allows us to use an optical tweezer to isolate cells with interesting phenotypes. We used the method to identify mutants with perturbations in replication initiation control in Escherichia coli, but it can in principle be used to identify genetic elements associated with any type of complex or dynamic single-cell phenotype.

Tropical dry evergreen forests (TDEFs) are a unique and highly threatened forest type of the dry tropics. Their restoration could be strengthened if native species demonstrate carbon sequestration comparable to widely used non-native trees. We assessed biodiversity and carbon sequestration in a restored TDEF in India, developed over 50 years from a largely barren landscape. The site now supports high woody-plant diversity, with 91 native species across 34 families. Aboveground biomass (AGB) averaged 66.91 +/- 41.2 Mg/ha comparable to seasonally dry tropical forests globally. Although native species were planted more recently and are shorter than non-natives, they contributed 23.86 +/- 23.4 Mg/ha to AGB and show potential for future increases in basal area. Given their comparable wood densities and capacity to attain similar heights, native species are predicted to sequester carbon at levels similar to non-natives in the long term. AGB was unrelated to species diversity. Overall, native TDEF species can achieve carbon storage while maintaining ecological integrity.