Toward a Predictive Understanding of Cyanobacterial Harmful Algal Blooms through AI Integration of Physical, Chemical, and Biological Data.

Freshwater cyanobacterial harmful algal blooms (cyanoHABs) are a worldwide problem resulting in substantial economic losses, due to harm to drinking water supplies, commercial fishing, wildlife, property values, recreation, and tourism. Moreover, toxins produced from some cyanoHABs threaten human and animal health. Climate warming can affect the distribution of cyanoHABs, where rising temperatures facilitate more intense blooms and a greater distribution of cyanoHABs in inland freshwater. Nutrient runoff from adjacent watersheds is also a major driver of cyanoHAB formation. While some of the physicochemical factors behind cyanoHAB dynamics are known, there are still major gaps in our understanding of the conditions that trigger and sustain cyanoHABs over time. In this perspective, we suggest that sufficient data sets, as well as machine learning (ML) and artificial intelligence (AI) tools, are available to build a comprehensive model of cyanoHAB dynamics based on integrated environmental/climate, nutrient/water chemistry, and cyanoHAB microbiome and 'omics data to identify key factors contributing to HAB formation, intensity, and toxicity. By taking a holistic approach to the analysis of all available data, including the rapidly growing number of biological data sets, we can provide the foundational knowledge needed to address the increasing threat of cyanoHABs to the security of our water resources.

Biodegradation Studies of Polyhydroxybutyrate and Polyhydroxybutyrate-co-Polyhydroxyvalerate Films in Soil.

Due to increased environmental pressures, significant research has focused on finding suitable biodegradable plastics to replace ubiquitous petrochemical-derived polymers. Polyhydroxyalkanoates (PHAs) are a class of polymers that can be synthesized by microorganisms and are biodegradable, making them suitable candidates. The present study looks at the degradation properties of two PHA polymers: polyhydroxybutyrate (PHB) and polyhydroxybutyrate-co-polyhydroxyvalerate (PHBV; 8 wt.% valerate), in two different soil conditions: soil fully saturated with water (100% relative humidity, RH) and soil with 40% RH. The degradation was evaluated by observing the changes in appearance, chemical signatures, mechanical properties, and molecular weight of samples. Both PHB and PHBV were degraded completely after two weeks in 100% RH soil conditions and showed significant reductions in mechanical properties after just three days. The samples in 40% RH soil, however, showed minimal changes in mechanical properties, melting temperatures/crystallinity, and molecular weight over six weeks. By observing the degradation behavior for different soil conditions, these results can pave the way for identifying situations where the current use of plastics can be replaced with biodegradable alternatives.

Nonclassical autophagy activation pathways are essential for production of infectious Influenza A virus in vitro.

Autophagy is a critical mechanism deployed by eukaryotic cells in response to stress, including viral infection, to boost the innate antimicrobial responses. However, an increasing number of pathogens hijack the autophagic machinery to facilitate their own replication. Influenza A virus (IAV), responsible for several global pandemics, has an intricate dependence on autophagy for successful replication in mammalian cells. To elucidate key chokepoints in the host stress responses facilitating IAV replication, we constructed a meta-transcriptome of IAV and host gene expression dynamics during early (1-3 hpi), mid (4-6 hpi), and late (8-12 hpi) stages of the viral replication cycle at two multiplicities of infection (MOI): 1 and 5. We supplemented the global transcriptome study with phosphoproteomic analysis of stress-activated protein kinase (SAPK/JNK) signaling in lung carcinoma (predominantly used as an in vitro model of IAV replication) and normal human bronchial epithelial cells. We report significant differences in the activation profiles of autophagy regulating genes upon IAV infection at the two MOI as well as divergent dependence on ULK1 signaling within the normal and cancer cells. Regardless of the cell model, JNK-Thr187 signaling was crucial for the production of infectious viral particles.

Inhibition of DNA Methylation in Picochlorum soloecismus Alters Algae Productivity.

Eukaryotic organisms regulate the organization, structure, and accessibility of their genomes through chromatin remodeling that can be inherited as epigenetic modifications. These DNA and histone protein modifications are ultimately responsible for an organism's molecular adaptation to the environment, resulting in distinctive phenotypes. Epigenetic manipulation of algae holds yet untapped potential for the optimization of biofuel production and bioproduct formation; however, epigenetic machinery and modes-of-action have not been well characterized in algae. We sought to determine the extent to which the biofuel platform species Picochlorum soloecismus utilizes DNA methylation to regulate its genome. We found candidate genes with domains for DNA methylation in the P. soloecismus genome. Whole-genome bisulfite sequencing revealed DNA methylation in all three cytosine contexts (CpG, CHH, and CHG). While global DNA methylation is low overall (∼1.15%), it occurs in appreciable quantities (12.1%) in CpG dinucleotides in a bimodal distribution in all genomic contexts, though terminators contain the greatest number of CpG sites per kilobase. The P. soloecismus genome becomes hypomethylated during the growth cycle in response to nitrogen starvation. Algae cultures were treated daily across the growth cycle with 20 µM 5-aza-2'-deoxycytidine (5AZA) to inhibit propagation of DNA methylation in daughter cells. 5AZA treatment significantly increased optical density and forward and side scatter of cells across the growth cycle (16 days). This increase in cell size and complexity correlated with a significant increase (∼66%) in lipid accumulation. Site specific CpG DNA methylation was significantly altered with 5AZA treatment over the time course, though nitrogen starvation itself induced significant hypomethylation in CpG contexts. Genes involved in several biological processes, including fatty acid synthesis, had altered methylation ratios in response to 5AZA; we hypothesize that these changes are potentially responsible for the phenotype of early induction of carbon storage as lipids. This is the first report to utilize epigenetic manipulation strategies to alter algal physiology and phenotype. Collectively, these data suggest these strategies can be utilized to fine-tune metabolic responses, alter growth, and enhance environmental adaption of microalgae for desired outcomes.

Mispacking and the Fitness Landscape of the Green Fluorescent Protein Chromophore Milieu.

The autocatalytic maturation of the chromophore in green fluorescent protein (GFP) was thought to require the precise positioning of the side chains surrounding it in the core of the protein, many of which are strongly conserved among homologous fluorescent proteins. In this study, we screened for green fluorescence in an exhaustive set of point mutations of seven residues that make up the chromophore microenvironment, excluding R96 and E222 because mutations at these positions have been previously characterized. Contrary to expectations, nearly all amino acids were tolerated at all seven positions. Only four point mutations knocked out fluorescence entirely. However, chromophore maturation was found to be slower and/or fluorescence reduced in several cases. Selected combinations of mutations showed nonadditive effects, including cooperativity and rescue. The results provide guidelines for the computational engineering of GFPs.

Toward Computationally Designed Self-Reporting Biosensors Using Leave-One-Out Green Fluorescent Protein.

Leave-one-out green fluorescent protein (LOOn-GFP) is a circularly permuted and truncated GFP lacking the nth ß-strand element. LOO7-GFP derived from the wild-type sequence (LOO7-WT) folds and reconstitutes fluorescence upon addition of ß-strand 7 (S7) as an exogenous peptide. Computational protein design may be used to modify the sequence of LOO7-GFP to fit a different peptide sequence, while retaining the reconstitution activity. Here we present a computationally designed leave-one-out GFP in which wild-type strand 7 has been replaced by a 12-residue peptide (HA) from the H5 antigenic region of the Thailand strain of H5N1 influenza virus hemagglutinin. The DEEdesign software was used to generate a sequence library with mutations at 13 positions around the peptide, coding for approximately 3 × 10(5) sequence combinations. The library was coexpressed with the HA peptide in E. coli and colonies were screened for in vivo fluorescence. Glowing colonies were sequenced, and one (LOO7-HA4) with 7 mutations was purified and characterized. LOO7-HA4 folds, fluoresces in vivo and in vitro, and binds HA. However, binding results in a decrease in fluorescence instead of the expected increase, caused by the peptide-induced dissociation of a novel, glowing oligomeric complex instead of the reconstitution of the native structure. Efforts to improve binding and recover reconstitution using in vitro evolution produced colonies that glowed brighter and matured faster. Two of these were characterized. One lost all affinity for the HA peptide but glowed more brightly in the unbound oligomeric state. The other increased in affinity to the HA peptide but still did not reconstitute the fully folded state. Despite failing to fold completely, peptide binding by computational design was observed and was improved by directed evolution. The ratio of HA to S7 binding increased from 0.0 for the wild-type sequence (no binding) to 0.01 after computational design (weak binding) and to 0.48 (comparable binding) after in vitro evolution. The novel oligomeric state is composed of an open barrel.

Exploring the folding pathway of green fluorescent protein through disulfide engineering.

We have introduced two disulfide crosslinks into the loop regions on opposite ends of the beta barrel in superfolder green fluorescent protein (GFP) in order to better understand the nature of its folding pathway. When the disulfide on the side opposite the N/C-termini is formed, folding is 2× faster, unfolding is 2000× slower, and the protein is stabilized by 16 kJ/mol. But when the disulfide bond on the side of the termini is formed we see little change in the kinetics and stability. The stabilization upon combining the two crosslinks is approximately additive. When the kinetic effects are broken down into multiple phases, we observe Hammond behavior in the upward shift of the kinetic m-value of unfolding. We use these results in conjunction with structural analysis to assign folding intermediates to two parallel folding pathways. The data are consistent with a view that the two fastest transition states of folding are "barrel closing" steps. The slower of the two phases passes through an intermediate with the barrel opening occurring between strands 7 and 8, while the faster phase opens between 9 and 4. We conclude that disulfide crosslink-induced perturbations in kinetics are useful for mapping the protein folding pathway.

The role of cross-chain ionic interactions for the stability of collagen model peptides.

The contribution of ionic interactions to the stability of the collagen triple helix was studied using molecular dynamics (MD) simulations and biophysical methods. To this end, we examined the stability of a host-guest collagen model peptide, Ac-GPOGPOGPYGXOGPOGPO-NH2, substituting KGE, KGD, EGK, and DGK for the YGX sequence. All-atom, implicit solvent MD simulations show that the fraction of cross-chain ionic interactions formed is different, with the most pronounced in the KGE and KGD sequences, and the least in the DGK sequence. To test whether the fraction of cross-chain ionic interactions correlates with the stability, experimental measurements of thermostability were done using differential scanning calorimetry and circular dichroism spectroscopy. It was found that the melting temperature is very similar for KGE and KGD peptides, whereas the EGK peptide has lower thermostability and the DGK peptide is the least thermostable. A novel, to our knowledge, computational protocol termed temperature-scan MD was applied to estimate the relative stabilities of the peptides from MD simulations. We found an excellent correlation between transition temperatures obtained from temperature-scan MD and those measured experimentally. These results suggest the importance of cross-chain ionic interactions for the stability of collagen triple helix and confirm the utility of MD simulations in predicting interactions and stability in this system.