Human antibody C10 neutralizes by diminishing Zika but enhancing dengue virus dynamics.

The human monoclonal antibody (HmAb) C10 potently cross-neutralizes Zika virus (ZIKV) and dengue virus. Analysis of antibody fragment (Fab) C10 interactions with ZIKV and dengue virus serotype 2 (DENV2) particles by cryoelectron microscopy (cryo-EM) and amide hydrogen/deuterium exchange mass spectrometry (HDXMS) shows that Fab C10 binding decreases overall ZIKV particle dynamics, whereas with DENV2, the same Fab causes increased dynamics. Testing of different Fab C10:DENV2 E protein molar ratios revealed that, at higher Fab ratios, especially at saturated concentrations, the Fab enhanced viral dynamics (detected by HDXMS), and observation under cryo-EM showed increased numbers of distorted particles. Our results suggest that Fab C10 stabilizes ZIKV but that with DENV2 particles, high Fab C10 occupancy promotes E protein dimer conformational changes leading to overall increased particle dynamics and distortion of the viral surface. This is the first instance of a broadly neutralizing antibody eliciting virus-specific increases in whole virus particle dynamics.

Long-Term Programming of CD8 T Cell Immunity by Perinatal Exposure to Glucocorticoids.

Early life environmental exposure, particularly during perinatal period, can have a life-long impact on organismal development and physiology. The biological rationale for this phenomenon is to promote physiological adaptations to the anticipated environment based on early life experience. However, perinatal exposure to adverse environments can also be associated with adult-onset disorders. Multiple environmental stressors induce glucocorticoids, which prompted us to investigate their role in developmental programming. Here, we report that perinatal glucocorticoid exposure had long-term consequences and resulted in diminished CD8 T cell response in adulthood and impaired control of tumor growth and bacterial infection. We found that perinatal glucocorticoid exposure resulted in persistent alteration of the hypothalamic-pituitary-adrenal (HPA) axis. Consequently, the level of the hormone in adults was significantly reduced, resulting in decreased CD8 T cell function. Our study thus demonstrates that perinatal stress can have long-term consequences on CD8 T cell immunity by altering HPA axis activity.

ECF-Type ATP-Binding Cassette Transporters.

Energy-coupling factor (ECF)-type ATP-binding cassette (ABC) transporters catalyze membrane transport of micronutrients in prokaryotes. Crystal structures and biochemical characterization have revealed that ECF transporters are mechanistically distinct from other ABC transport systems. Notably, ECF transporters make use of small integral membrane subunits (S-components) that are predicted to topple over in the membrane when carrying the bound substrate from the extracellular side of the bilayer to the cytosol. Here, we review the phylogenetic diversity of ECF transporters as well as recent structural and biochemical advancements that have led to the postulation of conceptually different mechanistic models. These models can be described as power stroke and thermal ratchet. Structural data indicate that the lipid composition and bilayer structure are likely to have great impact on the transport function. We argue that study of ECF transporters could lead to generic insight into membrane protein structure, dynamics, and interaction.

Molecular Profiling Reveals Biologically Discrete Subsets and Pathways of Progression in Diffuse Glioma.

Therapy development for adult diffuse glioma is hindered by incomplete knowledge of somatic glioma driving alterations and suboptimal disease classification. We defined the complete set of genes associated with 1,122 diffuse grade II-III-IV gliomas from The Cancer Genome Atlas and used molecular profiles to improve disease classification, identify molecular correlations, and provide insights into the progression from low- to high-grade disease. Whole-genome sequencing data analysis determined that ATRX but not TERT promoter mutations are associated with increased telomere length. Recent advances in glioma classification based on IDH mutation and 1p/19q co-deletion status were recapitulated through analysis of DNA methylation profiles, which identified clinically relevant molecular subsets. A subtype of IDH mutant glioma was associated with DNA demethylation and poor outcome; a group of IDH-wild-type diffuse glioma showed molecular similarity to pilocytic astrocytoma and relatively favorable survival. Understanding of cohesive disease groups may aid improved clinical outcomes.

The somatic genomic landscape of glioblastoma.

We describe the landscape of somatic genomic alterations based on multidimensional and comprehensive characterization of more than 500 glioblastoma tumors (GBMs). We identify several novel mutated genes as well as complex rearrangements of signature receptors, including EGFR and PDGFRA. TERT promoter mutations are shown to correlate with elevated mRNA expression, supporting a role in telomerase reactivation. Correlative analyses confirm that the survival advantage of the proneural subtype is conferred by the G-CIMP phenotype, and MGMT DNA methylation may be a predictive biomarker for treatment response only in classical subtype GBM. Integrative analysis of genomic and proteomic profiles challenges the notion of therapeutic inhibition of a pathway as an alternative to inhibition of the target itself. These data will facilitate the discovery of therapeutic and diagnostic target candidates, the validation of research and clinical observations and the generation of unanticipated hypotheses that can advance our molecular understanding of this lethal cancer.

SARS-CoV-2 Omicron variant replication in human bronchus and lung ex vivo.

The emergence of SARS-CoV-2 variants of concern with progressively increased transmissibility between humans is a threat to global public health. The Omicron variant of SARS-CoV-2 also evades immunity from natural infection or vaccines1, but it is unclear whether its exceptional transmissibility is due to immune evasion or intrinsic virological properties. Here we compared the replication competence and cellular tropism of the wild-type virus and the D614G, Alpha (B.1.1.7), Beta (B.1.351), Delta (B.1.617.2) and Omicron (B.1.1.529) variants in ex vivo explant cultures of human bronchi and lungs. We also evaluated the dependence on TMPRSS2 and cathepsins for infection. We show that Omicron replicates faster than all other SARS-CoV-2 variants studied in the bronchi but less efficiently in the lung parenchyma. All variants of concern have similar cellular tropism compared to the wild type. Omicron is more dependent on cathepsins than the other variants of concern tested, suggesting that the Omicron variant enters cells through a different route compared with the other variants. The lower replication competence of Omicron in the human lungs may explain the reduced severity of Omicron that is now being reported in epidemiological studies, although determinants of severity are multifactorial. These findings provide important biological correlates to previous epidemiological observations.

Imputation accuracy across global human populations.

Genotype imputation is now fundamental for genome-wide association studies but lacks fairness due to the underrepresentation of references from non-European ancestries. The state-of-the-art imputation reference panel released by the Trans-Omics for Precision Medicine (TOPMed) initiative improved the imputation of admixed African-ancestry and Hispanic/Latino samples, but imputation for populations primarily residing outside of North America may still fall short in performance due to persisting underrepresentation. To illustrate this point, we imputed the genotypes of over 43,000 individuals across 123 populations around the world and identified numerous populations where imputation accuracy paled in comparison to that of European-ancestry populations. For instance, the mean imputation r-squared (Rsq) for variants with minor allele frequencies between 1% and 5% in Saudi Arabians (n = 1,061), Vietnamese (n = 1,264), Thai (n = 2,435), and Papua New Guineans (n = 776) were 0.79, 0.78, 0.76, and 0.62, respectively, compared to 0.90-0.93 for comparable European populations matched in sample size and SNP array content. Outside of Africa and Latin America, Rsq appeared to decrease as genetic distances to European-ancestry reference increased, as predicted. Using sequencing data as ground truth, we also showed that Rsq may over-estimate imputation accuracy for non-European populations more than European populations, suggesting further disparity in accuracy between populations. Using 1,496 sequenced individuals from Taiwan Biobank as a second reference panel to TOPMed, we also assessed a strategy to improve imputation for non-European populations with meta-imputation, but this design did not improve accuracy across frequency spectra. Taken together, our analyses suggest that we must ultimately strive to increase diversity and size to promote equity within genetics research.

Genomic origin, fragmentomics, and transcriptional properties of long cell-free DNA molecules in human plasma.

Recent studies have revealed an unexplored population of long cell-free DNA (cfDNA) molecules in human plasma using long-read sequencing technologies. However, the biological properties of long cfDNA molecules (>500 bp) remain largely unknown. To this end, we have investigated the origins of long cfDNA molecules from different genomic elements. Analysis of plasma cfDNA using long-read sequencing reveals an uneven distribution of long molecules from across the genome. Long cfDNA molecules show overrepresentation in euchromatic regions of the genome, in sharp contrast to short DNA molecules. We observe a stronger relationship between the abundance of long molecules and mRNA gene expression levels, compared with short molecules (Pearson's r = 0.71 vs. -0.14). Moreover, long and short molecules show distinct fragmentation patterns surrounding CpG sites. Leveraging the cleavage preferences surrounding CpG sites, the combined cleavage ratios of long and short molecules can differentiate patients with hepatocellular carcinoma (HCC) from non-HCC subjects (AUC = 0.87). We also investigated knockout mice in which selected nuclease genes had been inactivated in comparison with wild-type mice. The proportion of long molecules originating from transcription start sites are lower in Dffb-deficient mice but higher in Dnase1l3-deficient mice compared with that of wild-type mice. This work thus provides new insights into the biological properties and potential clinical applications of long cfDNA molecules.

PKM2 phosphorylates histone H3 and promotes gene transcription and tumorigenesis.

Tumor-specific pyruvate kinase M2 (PKM2) is essential for the Warburg effect. In addition to its well-established role in aerobic glycolysis, PKM2 directly regulates gene transcription. However, the mechanism underlying this nonmetabolic function of PKM2 remains elusive. We show here that PKM2 directly binds to histone H3 and phosphorylates histone H3 at T11 upon EGF receptor activation. This phosphorylation is required for the dissociation of HDAC3 from the CCND1 and MYC promoter regions and subsequent acetylation of histone H3 at K9. PKM2-dependent histone H3 modifications are instrumental in EGF-induced expression of cyclin D1 and c-Myc, tumor cell proliferation, cell-cycle progression, and brain tumorigenesis. In addition, levels of histone H3 T11 phosphorylation correlate with nuclear PKM2 expression levels, glioma malignancy grades, and prognosis. These findings highlight the role of PKM2 as a protein kinase in its nonmetabolic functions of histone modification, which is essential for its epigenetic regulation of gene expression and tumorigenesis.

Convergent somatic mutations in metabolism genes in chronic liver disease.

The progression of chronic liver disease to hepatocellular carcinoma is caused by the acquisition of somatic mutations that affect 20-30 cancer genes1-8. Burdens of somatic mutations are higher and clonal expansions larger in chronic liver disease9-13 than in normal liver13-16, which enables positive selection to shape the genomic landscape9-13. Here we analysed somatic mutations from 1,590 genomes across 34 liver samples, including healthy controls, alcohol-related liver disease and non-alcoholic fatty liver disease. Seven of the 29 patients with liver disease had mutations in FOXO1, the major transcription factor in insulin signalling. These mutations affected a single hotspot within the gene, impairing the insulin-mediated nuclear export of FOXO1. Notably, six of the seven patients with FOXO1S22W hotspot mutations showed convergent evolution, with variants acquired independently by up to nine distinct hepatocyte clones per patient. CIDEB, which regulates lipid droplet metabolism in hepatocytes17-19, and GPAM, which produces storage triacylglycerol from free fatty acids20,21, also had a significant excess of mutations. We again observed frequent convergent evolution: up to fourteen independent clones per patient with CIDEB mutations and up to seven clones per patient with GPAM mutations. Mutations in metabolism genes were distributed across multiple anatomical segments of the liver, increased clone size and were seen in both alcohol-related liver disease and non-alcoholic fatty liver disease, but rarely in hepatocellular carcinoma. Master regulators of metabolic pathways are a frequent target of convergent somatic mutation in alcohol-related and non-alcoholic fatty liver disease.

SARS-CoV-2-specific CD8+ T cells from people with long COVID establish and maintain effector phenotype and key TCR signatures over 2 years.

Long COVID occurs in a small but important minority of patients following COVID-19, reducing quality of life and contributing to healthcare burden. Although research into underlying mechanisms is evolving, immunity is understudied. SARS-CoV-2-specific T cell responses are of key importance for viral clearance and COVID-19 recovery. However, in long COVID, the establishment and persistence of SARS-CoV-2-specific T cells are far from clear, especially beyond 12 mo postinfection and postvaccination. We defined ex vivo antigen-specific B cell and T cell responses and their T cell receptors (TCR) repertoires across 2 y postinfection in people with long COVID. Using 13 SARS-CoV-2 peptide-HLA tetramers, spanning 11 HLA allotypes, as well as spike and nucleocapsid probes, we tracked SARS-CoV-2-specific CD8+ and CD4+ T cells and B-cells in individuals from their first SARS-CoV-2 infection through primary vaccination over 24 mo. The frequencies of ORF1a- and nucleocapsid-specific T cells and B cells remained stable over 24 mo. Spike-specific CD8+ and CD4+ T cells and B cells were boosted by SARS-CoV-2 vaccination, indicating immunization, in fully recovered and people with long COVID, altered the immunodominance hierarchy of SARS-CoV-2 T cell epitopes. Meanwhile, influenza-specific CD8+ T cells were stable across 24 mo, suggesting no bystander-activation. Compared to total T cell populations, SARS-CoV-2-specific T cells were enriched for central memory phenotype, although the proportion of central memory T cells decreased following acute illness. Importantly, TCR repertoire composition was maintained throughout long COVID, including postvaccination, to 2 y postinfection. Overall, we defined ex vivo SARS-CoV-2-specific B cells and T cells to understand primary and recall responses, providing key insights into antigen-specific responses in people with long COVID.

Tree-based QTL mapping with expected local genetic relatedness matrices.

Understanding the genetic basis of complex phenotypes is a central pursuit of genetics. Genome-wide association studies (GWASs) are a powerful way to find genetic loci associated with phenotypes. GWASs are widely and successfully used, but they face challenges related to the fact that variants are tested for association with a phenotype independently, whereas in reality variants at different sites are correlated because of their shared evolutionary history. One way to model this shared history is through the ancestral recombination graph (ARG), which encodes a series of local coalescent trees. Recent computational and methodological breakthroughs have made it feasible to estimate approximate ARGs from large-scale samples. Here, we explore the potential of an ARG-based approach to quantitative-trait locus (QTL) mapping, echoing existing variance-components approaches. We propose a framework that relies on the conditional expectation of a local genetic relatedness matrix (local eGRM) given the ARG. Simulations show that our method is especially beneficial for finding QTLs in the presence of allelic heterogeneity. By framing QTL mapping in terms of the estimated ARG, we can also facilitate the detection of QTLs in understudied populations. We use local eGRM to analyze two chromosomes containing known body size loci in a sample of Native Hawaiians. Our investigations can provide intuition about the benefits of using estimated ARGs in population- and statistical-genetic methods in general.

Estimating heritability explained by local ancestry and evaluating stratification bias in admixture mapping from summary statistics.

The heritability explained by local ancestry markers in an admixed population (hγ2) provides crucial insight into the genetic architecture of a complex disease or trait. Estimation of hγ2 can be susceptible to biases due to population structure in ancestral populations. Here, we present heritability estimation from admixture mapping summary statistics (HAMSTA), an approach that uses summary statistics from admixture mapping to infer heritability explained by local ancestry while adjusting for biases due to ancestral stratification. Through extensive simulations, we demonstrate that HAMSTA hγ2 estimates are approximately unbiased and are robust to ancestral stratification compared to existing approaches. In the presence of ancestral stratification, we show a HAMSTA-derived sampling scheme provides a calibrated family-wise error rate (FWER) of ∼5% for admixture mapping, unlike existing FWER estimation approaches. We apply HAMSTA to 20 quantitative phenotypes of up to 15,988 self-reported African American individuals in the Population Architecture using Genomics and Epidemiology (PAGE) study. We observe hˆγ2 in the 20 phenotypes range from 0.0025 to 0.033 (mean hˆγ2 = 0.012 ± 9.2 × 10-4), which translates to hˆ2 ranging from 0.062 to 0.85 (mean hˆ2 = 0.30 ± 0.023). Across these phenotypes we find little evidence of inflation due to ancestral population stratification in current admixture mapping studies (mean inflation factor of 0.99 ± 0.001). Overall, HAMSTA provides a fast and powerful approach to estimate genome-wide heritability and evaluate biases in test statistics of admixture mapping studies.

scDecouple: decoupling cellular response from infected proportion bias in scCRISPR-seq.

Single-cell clustered regularly interspaced short palindromic repeats-sequencing (scCRISPR-seq) is an emerging high-throughput CRISPR screening technology where the true cellular response to perturbation is coupled with infected proportion bias of guide RNAs (gRNAs) across different cell clusters. The mixing of these effects introduces noise into scCRISPR-seq data analysis and thus obstacles to relevant studies. We developed scDecouple to decouple true cellular response of perturbation from the influence of infected proportion bias. scDecouple first models the distribution of gene expression profiles in perturbed cells and then iteratively finds the maximum likelihood of cell cluster proportions as well as the cellular response for each gRNA. We demonstrated its performance in a series of simulation experiments. By applying scDecouple to real scCRISPR-seq data, we found that scDecouple enhances the identification of biologically perturbation-related genes. scDecouple can benefit scCRISPR-seq data analysis, especially in the case of heterogeneous samples or complex gRNA libraries.

Fragmentation landscape of cell-free DNA revealed by deconvolutional analysis of end motifs.

Cell-free DNA (cfDNA) fragmentation is nonrandom, at least partially mediated by various DNA nucleases, forming characteristic cfDNA end motifs. However, there is a paucity of tools for deciphering the relative contributions of cfDNA cleavage patterns related to underlying fragmentation factors. In this study, through non-negative matrix factorization algorithm, we used 256 5' 4-mer end motifs to identify distinct types of cfDNA cleavage patterns, referred to as "founder" end-motif profiles (F-profiles). F-profiles were associated with different DNA nucleases based on whether such patterns were disrupted in nuclease-knockout mouse models. Contributions of individual F-profiles in a cfDNA sample could be determined by deconvolutional analysis. We analyzed 93 murine cfDNA samples of different nuclease-deficient mice and identified six types of F-profiles. F-profiles I, II, and III were linked to deoxyribonuclease 1 like 3 (DNASE1L3), deoxyribonuclease 1 (DNASE1), and DNA fragmentation factor subunit beta (DFFB), respectively. We revealed that 42.9% of plasma cfDNA molecules were attributed to DNASE1L3-mediated fragmentation, whereas 43.4% of urinary cfDNA molecules involved DNASE1-mediated fragmentation. We further demonstrated that the relative contributions of F-profiles were useful to inform pathological states, such as autoimmune disorders and cancer. Among the six F-profiles, the use of F-profile I could inform the human patients with systemic lupus erythematosus. F-profile VI could be used to detect individuals with hepatocellular carcinoma, with an area under the receiver operating characteristic curve of 0.97. F-profile VI was more prominent in patients with nasopharyngeal carcinoma undergoing chemoradiotherapy. We proposed that this profile might be related to oxidative stress.

The Next Frontier in Noninvasive Prenatal Diagnostics: Cell-Free Fetal DNA Analysis for Monogenic Disease Assessment.

With the widespread clinical adoption of noninvasive screening for fetal chromosomal aneuploidies based on cell-free DNA analysis from maternal plasma, more researchers are turning their attention to noninvasive prenatal assessment for single-gene disorders. The development of a spectrum of approaches to analyze cell-free DNA in maternal circulation, including relative mutation dosage, relative haplotype dosage, and size-based methods, has expanded the scope of noninvasive prenatal testing to sex-linked and autosomal recessive disorders. Cell-free fetal DNA analysis for several of the more prevalent single-gene disorders has recently been introduced into clinical service. This article reviews the analytical approaches currently available and discusses the extent of the clinical implementation of noninvasive prenatal testing for single-gene disorders.

A genealogical estimate of genetic relationships.

The application of genetic relationships among individuals, characterized by a genetic relationship matrix (GRM), has far-reaching effects in human genetics. However, the current standard to calculate the GRM treats linked markers as independent and does not explicitly model the underlying genealogical history of the study sample. Here, we propose a coalescent-informed framework, namely the expected GRM (eGRM), to infer the expected relatedness between pairs of individuals given an ancestral recombination graph (ARG) of the sample. Through extensive simulations, we show that the eGRM is an unbiased estimate of latent pairwise genome-wide relatedness and is robust when computed with ARG inferred from incomplete genetic data. As a result, the eGRM better captures the structure of a population than the canonical GRM, even when using the same genetic information. More importantly, our framework allows a principled approach to estimate the eGRM at different time depths of the ARG, thereby revealing the time-varying nature of population structure in a sample. When applied to SNP array genotypes from a population sample from Northern and Eastern Finland, we find that clustering analysis with the eGRM reveals population structure driven by subpopulations that would not be apparent via the canonical GRM and that temporally the population model is consistent with recent divergence and expansion. Taken together, our proposed eGRM provides a robust tree-centric estimate of relatedness with wide application to genetic studies.

Effects of rare kidney diseases on kidney failure: a longitudinal analysis of the UK National Registry of Rare Kidney Diseases (RaDaR) cohort.

BACKGROUND: Individuals with rare kidney diseases account for 5-10% of people with chronic kidney disease, but constitute more than 25% of patients receiving kidney replacement therapy. The National Registry of Rare Kidney Diseases (RaDaR) gathers longitudinal data from patients with these conditions, which we used to study disease progression and outcomes of death and kidney failure. METHODS: People aged 0-96 years living with 28 types of rare kidney diseases were recruited from 108 UK renal care facilities. The primary outcomes were cumulative incidence of mortality and kidney failure in individuals with rare kidney diseases, which were calculated and compared with that of unselected patients with chronic kidney disease. Cumulative incidence and Kaplan-Meier survival estimates were calculated for the following outcomes: median age at kidney failure; median age at death; time from start of dialysis to death; and time from diagnosis to estimated glomerular filtration rate (eGFR) thresholds, allowing calculation of time from last eGFR of 75 mL/min per 1·73 m2 or more to first eGFR of less than 30 mL/min per 1·73 m2 (the therapeutic trial window). FINDINGS: Between Jan 18, 2010, and July 25, 2022, 27 285 participants were recruited to RaDaR. Median follow-up time from diagnosis was 9·6 years (IQR 5·9-16·7). RaDaR participants had significantly higher 5-year cumulative incidence of kidney failure than 2·81 million UK patients with all-cause chronic kidney disease (28% vs 1%; p<0·0001), but better survival rates (standardised mortality ratio 0·42 [95% CI 0·32-0·52]; p<0·0001). Median age at kidney failure, median age at death, time from start of dialysis to death, time from diagnosis to eGFR thresholds, and therapeutic trial window all varied substantially between rare diseases. INTERPRETATION: Patients with rare kidney diseases differ from the general population of individuals with chronic kidney disease: they have higher 5-year rates of kidney failure but higher survival than other patients with chronic kidney disease stages 3-5, and so are over-represented in the cohort of patients requiring kidney replacement therapy. Addressing unmet therapeutic need for patients with rare kidney diseases could have a large beneficial effect on long-term kidney replacement therapy demand. FUNDING: RaDaR is funded by the Medical Research Council, Kidney Research UK, Kidney Care UK, and the Polycystic Kidney Disease Charity.

Activation of caspase-1 by the NLRP3 inflammasome regulates the NADPH oxidase NOX2 to control phagosome function.

Phagocytosis is a fundamental cellular process that is pivotal for immunity as it coordinates microbial killing, innate immune activation and antigen presentation. An essential step in this process is phagosome acidification, which regulates many functions of these organelles that allow phagosomes to participate in processes that are essential to both innate and adaptive immunity. Here we report that acidification of phagosomes containing Gram-positive bacteria is regulated by the NLRP3 inflammasome and caspase-1. Active caspase-1 accumulates on phagosomes and acts locally to control the pH by modulating buffering by the NADPH oxidase NOX2. These data provide insight into a mechanism by which innate immune signals can modify cellular defenses and establish a new function for the NLRP3 inflammasome and caspase-1 in host defense.

Creating New Antifoulants Using the Tools and Tactics of Medicinal Chemistry.

The unwanted accumulation of marine micro- and macroorganisms such as algae and barnacles on submerged man-made structures and vessel hulls is a major challenge for any marine operation. Known as biofouling, this problem leads to reduced hydrodynamic efficiency, significantly increased fuel usage, microbially induced corrosion, and, if not managed appropriately, eventual loss of both performance and structural integrity. Ship hull biofouling in the international maritime transport network conservatively accounts for 0.6% of global carbon emissions, highlighting the global scale and the importance of this problem. Improved antifouling strategies to limit surface colonization are paramount for essential activities such as shipping, aquaculture, desalination, and the marine renewable energy sector, representing both a multibillion dollar cost and a substantial practical challenge. From an ecological perspective, biofouling is a primary contributor to the global spread of invasive marine species, which has extensive implications for the marine environment.Historically, heavy metal-based toxic biocides have been used to control biofouling. However, their unwanted collateral ecological damage on nontarget species and bioaccumulation has led to recent global bans. With expanding human activities within aquaculture and offshore energy, it is both urgent and apparent that environmentally friendly surface protection remains key for maintaining the function of both moving and stationary marine structures. Biofouling communities are typically a highly complex network of both micro- and macroorganisms, representing a broad section of life from bacteria to macrophytes and animals. Given this diversity, it is unrealistic to expect that a single antifouling "silver bullet" will prevent colonization with the exception of generally toxic biocides. For that reason, modern and future antifouling solutions are anticipated to rely on novel coating technologies and "combination therapies" where mixtures of narrow-spectrum bioactive components are used to provide coverage across fouling species. In contrast to the existing cohort of outdated, toxic antifouling strategies, such as copper- and tributyltin-releasing paints, modern drug discovery techniques are increasingly being employed for the rational design of effective yet safe alternatives. The challenge for a medicinal chemistry approach is to effectively account for the large taxonomic diversity among fouling organisms combined with a lack of well-defined conserved molecular targets within most taxa.The current Account summarizes our work employing the tools of modern medicinal chemistry to discover, modify, and develop optimized and scalable antifouling solutions based on naturally occurring antifouling and repelling compounds from both marine and terrestrial sources. Inspiration for rational design comes from targeted studies on allelopathic natural products, natural repelling peptides, and secondary metabolites from sessile marine organisms with clean exteriors, which has yielded several efficient and promising antifouling leads.