Diagnosing Frontal Dynamics From Observations Using a Variational Approach

Intensive hydrographic and horizontal velocity measurements collected in the Alboran Sea enabled us to diagnose the three-dimensional dynamics of a frontal system. The sampled domain was characterized by a 40 km diameter anticyclonic eddy, with an intense front on its eastern side, separating the Atlantic and Mediterranean waters. Here, we implemented a multi-variate variational analysis (VA) to reconstruct the hydrographic fields, combining the 1-km horizontal resolution of the Underway Conductivity-Temperature-Depth (CTD) system with information on the flow shape from the Acoustic Doppler Current Profiler velocities. One advantage of the VA is given by the physical constraint, which preserves fine-scale gradients better than the classical optimal interpolation (OI). A comparison between real drifter trajectories and virtual particles advected in the mapping quantified the improvements in the VA over the OI, with a 15% larger skill score. Quasi-geostrophic (QG) and semi-geostrophic (SG) omega equations enabled us to estimate the vertical velocity (w) which reached 40 m/day on the dense side of the front. How nutrients and other passive tracers leave the mixed-layer and subduct is estimated with 3D advection from the VA, which agreed with biological sampling from traditional CTD casts at two eddy locations. Downwelling warm filaments are further evidence of subduction, in line with the w from SG, but not with QG. SG better accounted for the along-isopycnal component of w in agreement with another analysis made on isopycnal coordinates. The multi-platform approach of this work and the use of variational methods improved the characterization and understanding of (sub)-mesoscale frontal dynamics.This research was supported by the Office of Naval Research Departmental Research Initiative CALYPSO under program officers Terri Paluszkiewicz and Scott Harper. The authors' ONR Grant are as follows: N000141613130 (AP, SR and AM), N000141812418 (PMP), S. Johnston N000141812416 (TMSJ), N000141812138 (TO), N000141712517 and N00014191269 (LRC), N000141812139 and N000141812420 (AS) and N000141812139and (EDA). This article is also a contribution to the PRE-SWOT project funded by the Spanish Research Agency and the European Regional Development Fund (AEI/FEDER, UE) under grant agreement (CTM2016-78607-P)

Integrating genetic and oral histories of Southwest Indian populations

India is home to thousands of ethno-linguistically distinct groups, many maintaining strong self-identities that derive from oral traditions and histories. However, these traditions and histories are only partially documented and are in danger of being lost over time. More recently, genetic studies have established the existence of ancestry gradients derived from both western and eastern Eurasia as well as evidence of practices such as endogamy and consanguinity, revealing complexity in the regional population structure with consequences for the health landscape of local populations. Despite the increase in genome-wide data from India, there is still sparse sampling across finer-scale geographic regions leading to gaps in our understanding of how and when present-day genetic structure came into existence. To address the gaps in genetic and oral histories, we analyzed whole-genome sequences of 70 individuals from Southwest India identifying as Bunt, Kodava, and Nair—populations that share unique oral histories and origin narratives—and 78 recent immigrants to the United States with Kodava ancestry as part of a community-led initiative. We additionally generated genome-wide data from 10 individuals self-identifying as Kapla, a population from the same region that is socio-culturally different to the other three study populations. We supplemented existing but limited anthropological records on these populations with oral history accounts narrated by community members and non-member contacts during sampling and subsequent community engagement. Overall, we find that components of genetic ancestry are relatively homogeneous among the Bunt, Kodava, and Nair populations and comparable to neighboring populations in India, which motivates further investigation of non-local origin narratives referenced in their oral histories. A notable exception is the Kapla population, with a higher proportion of ancestry represented in the Onge from the Andaman Islands, similar to several South Indian tribal populations. Utilizing haplotype-based methods, we find latent genetic structure across South India, including the sampled populations available under aCC-BY-NC-ND 4.0 International license.was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made bioRxiv preprint doi: https://doi.org/10.1101/2022.07.06.498959; this version posted July 7, 2022. The copyright holder for this preprint (which 2 from Southwest India, suggesting more recent population structure between geographically proximal populations in the region. This study represents an attempt for community-engaged anthropological and genetic investigations in India and presents results from both sources, underscoring the need to recognize that oral and genetic histories should not be expected to overlap. Ultimately, oral traditions and unique self-identities, such as those held close by some of the study populations, warrant more community-driven anthropological investigations to better understand how they originate and their relationship to genetic histories

Tidal modulation of infragravity waves via nonlinear energy losses in the surfzone

Author Posting. © American Geophysical Union, 2006. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geophysical Research Letters 33 (2006): L05601, doi:10.1029/2005GL025514.The strong tidal modulation of infragravity (200 to 20 s period) waves observed on the southern California shelf is shown to be the result of nonlinear transfers of energy from these low-frequency long waves to higher-frequency motions. The energy loss occurs in the surfzone, and is stronger as waves propagate over the convex low-tide beach profile than over the concave high-tide profile, resulting in a tidal modulation of seaward-radiated infragravity energy. Although previous studies have attributed infragravity energy losses in the surfzone to bottom drag and turbulence, theoretical estimates using both observations and numerical simulations suggest nonlinear transfers dominate. The observed beach profiles and energy transfers are similar along several km of the southern California coast, providing a mechanism for the tidal modulation of infragravity waves observed in bottom-pressure and seismic records on the continental shelf and in the deep ocean.Support was provided by ONR and NSF

Mapping interactions with the chaperone network reveals factors that protect against tau aggregation.

A network of molecular chaperones is known to bind proteins ('clients') and balance their folding, function and turnover. However, it is often unclear which chaperones are critical for selective recognition of individual clients. It is also not clear why these key chaperones might fail in protein-aggregation diseases. Here, we utilized human microtubule-associated protein tau (MAPT or tau) as a model client to survey interactions between ~30 purified chaperones and ~20 disease-associated tau variants (~600 combinations). From this large-scale analysis, we identified human DnaJA2 as an unexpected, but potent, inhibitor of tau aggregation. DnaJA2 levels were correlated with tau pathology in human brains, supporting the idea that it is an important regulator of tau homeostasis. Of note, we found that some disease-associated tau variants were relatively immune to interactions with chaperones, suggesting a model in which avoiding physical recognition by chaperone networks may contribute to disease

Stratification of co-evolving genomic groups using ranked phylogenetic profiles

<p>Abstract</p> <p>Background</p> <p>Previous methods of detecting the taxonomic origins of arbitrary sequence collections, with a significant impact to genome analysis and in particular metagenomics, have primarily focused on compositional features of genomes. The evolutionary patterns of phylogenetic distribution of genes or proteins, represented by phylogenetic profiles, provide an alternative approach for the detection of taxonomic origins, but typically suffer from low accuracy. Herein, we present <it>rank-BLAST</it>, a novel approach for the assignment of protein sequences into genomic groups of the same taxonomic origin, based on the ranking order of phylogenetic profiles of target genes or proteins across the reference database.</p> <p>Results</p> <p>The rank-BLAST approach is validated by computing the phylogenetic profiles of all sequences for five distinct microbial species of varying degrees of phylogenetic proximity, against a reference database of 243 fully sequenced genomes. The approach - a combination of sequence searches, statistical estimation and clustering - analyses the degree of sequence divergence between sets of protein sequences and allows the classification of protein sequences according to the species of origin with high accuracy, allowing taxonomic classification of 64% of the proteins studied. In most cases, a main cluster is detected, representing the corresponding species. Secondary, functionally distinct and species-specific clusters exhibit different patterns of phylogenetic distribution, thus flagging gene groups of interest. Detailed analyses of such cases are provided as examples.</p> <p>Conclusion</p> <p>Our results indicate that the rank-BLAST approach can capture the taxonomic origins of sequence collections in an accurate and efficient manner. The approach can be useful both for the analysis of genome evolution and the detection of species groups in metagenomics samples.</p

Protein coalitions in a core mammalian biochemical network linked by rapidly evolving proteins

<p>Abstract</p> <p>Background</p> <p>Cellular ATP levels are generated by glucose-stimulated mitochondrial metabolism and determine metabolic responses, such as glucose-stimulated insulin secretion (GSIS) from the β-cells of pancreatic islets. We describe an analysis of the evolutionary processes affecting the core enzymes involved in glucose-stimulated insulin secretion in mammals. The proteins involved in this system belong to ancient enzymatic pathways: glycolysis, the TCA cycle and oxidative phosphorylation.</p> <p>Results</p> <p>We identify two sets of proteins, or protein coalitions, in this group of 77 enzymes with distinct evolutionary patterns. Members of the glycolysis, TCA cycle, metabolite transport, pyruvate and NADH shuttles have low rates of protein sequence evolution, as inferred from a human-mouse comparison, and relatively high rates of evolutionary gene duplication. Respiratory chain and glutathione pathway proteins evolve faster, exhibiting lower rates of gene duplication. A small number of proteins in the system evolve significantly faster than co-pathway members and may serve as rapidly evolving adapters, linking groups of co-evolving genes.</p> <p>Conclusions</p> <p>Our results provide insights into the evolution of the involved proteins. We find evidence for two coalitions of proteins and the role of co-adaptation in protein evolution is identified and could be used in future research within a functional context.</p

Informatics Technology Mimics Ecology: Dense, Mutualistic Collaboration Networks Are Associated with Higher Publication Rates

Information technology (IT) adoption enables biomedical research. Publications are an accepted measure of research output, and network models can describe the collaborative nature of publication. In particular, ecological networks can serve as analogies for publication and technology adoption. We constructed network models of adoption of bioinformatics programming languages and health IT (HIT) from the literature

Decoupling Environment-Dependent and Independent Genetic Robustness across Bacterial Species

The evolutionary origins of genetic robustness are still under debate: it may arise as a consequence of requirements imposed by varying environmental conditions, due to intrinsic factors such as metabolic requirements, or directly due to an adaptive selection in favor of genes that allow a species to endure genetic perturbations. Stratifying the individual effects of each origin requires one to study the pertaining evolutionary forces across many species under diverse conditions. Here we conduct the first large-scale computational study charting the level of robustness of metabolic networks of hundreds of bacterial species across many simulated growth environments. We provide evidence that variations among species in their level of robustness reflect ecological adaptations. We decouple metabolic robustness into two components and quantify the extents of each: the first, environmental-dependent, is responsible for at least 20% of the non-essential reactions and its extent is associated with the species' lifestyle (specialized/generalist); the second, environmental-independent, is associated (correlation = ∼0.6) with the intrinsic metabolic capacities of a species—higher robustness is observed in fast growers or in organisms with an extensive production of secondary metabolites. Finally, we identify reactions that are uniquely susceptible to perturbations in human pathogens, potentially serving as novel drug-targets