Differential responses of SARS-CoV-2 variants to environmental drivers during their selective sweeps.

Previous work has shown that environmental variables affect SARS-CoV-2 transmission, but it is unclear whether different strains show similar environmental responses. Here we leverage genetic data on the transmission of three (Alpha, Delta and Omicron BA.1) variants of SARS-CoV-2 throughout England, to unpick the roles that climate and public-health interventions play in the circulation of this virus. We find evidence for enhanced transmission of the virus in colder conditions in the first variant selective sweep (of Alpha, in winter), but limited evidence of an impact of climate in either the second (of Delta, in the summer, when vaccines were prevalent) or third sweep (of Omicron, in the winter, during a successful booster-vaccination campaign). We argue that the results for Alpha are to be expected if the impact of climate is non-linear: we find evidence of an asymptotic impact of temperature on the alpha variant transmission rate. That is, at lower temperatures, the influence of temperature on transmission is much higher than at warmer temperatures. As with the initial spread of SARS-CoV-2, however, the overwhelming majority of variation in disease transmission is explained by the intrinsic biology of the virus and public-health mitigation measures. Specifically, when vaccination rates are high, a major driver of the spread of a new variant is it's ability to evade immunity, and any climate effects are secondary (as evidenced for Delta and Omicron). Climate alone cannot describe the transmission dynamics of emerging SARS-CoV-2 variants.

Similar rates of reoperation for neuroma after transtibial amputations with and without targeted muscle reinnervation.

Objective: To compare the rates of revision surgery for symptomatic neuromas in patients undergoing primary transtibial amputations with and without targeted muscle reinnervation (TMR). Design: Retrospective cohort study. Setting: Level I trauma hospital and tertiary military medical center. Patients/Participants: Adult patients undergoing transtibial amputations with and without TMR. Intervention: Transtibial amputation with targeted muscle reinnervation. Main Outcome Measurements: Reoperation for symptomatic neuroma. Results: During the study period, there were 112 primary transtibial amputations performed, 29 with TMR and 83 without TMR. Over the same period, there were 51 revision transtibial amputations performed, including 23 (21%) in the patients undergoing primary transtibial amputation at the study institution. The most common indications for revision surgery were wound breakdown/dehiscence (42%, n = 25), followed by symptomatic neuroma 18% (n = 9/51) and infection/osteomyelitis (17%, n = 10) as the most common indications. However, of the patients undergoing primary amputation at the study's institution, there was no difference in reoperation rates for neuroma when comparing the TMR group (3.6%, n = 1/28) and no TMR group (4.0%, n = 3/75) (P = 0.97). Conclusions: Symptomatic neuroma is one of the most common reasons for revision amputation; however, this study was unable to demonstrate a difference in revision surgery rates for neuroma for patients undergoing primary transtibial amputation with or without targeted muscle reinnervation. Level of Evidence: Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.

High-throughput characterization of bacterial responses to complex mixtures of chemical pollutants.

Our understanding of how microbes respond to micropollutants, such as pesticides, is almost wholly based on single-species responses to individual chemicals. However, in natural environments, microbes experience multiple pollutants simultaneously. Here we perform a matrix of multi-stressor experiments by assaying the growth of model and non-model strains of bacteria in all 255 combinations of 8 chemical stressors (antibiotics, herbicides, fungicides and pesticides). We found that bacterial strains responded in different ways to stressor mixtures, which could not be predicted simply from their phylogenetic relatedness. Increasingly complex chemical mixtures were both more likely to negatively impact bacterial growth in monoculture and more likely to reveal net interactive effects. A mixed co-culture of strains proved more resilient to increasingly complex mixtures and revealed fewer interactions in the growth response. These results show predictability in microbial population responses to chemical stressors and could increase the utility of next-generation eco-toxicological assays.

Identification and engineering of potent cyclic peptides with selective or promiscuous binding through biochemical profiling and bioinformatic data analysis.

As our understanding of biological systems grows, so does the need to selectively target individual or multiple members of specific protein families in order to probe their function. Many targets of current biological and pharmaceutical interest are part of a large family of closely related proteins and achieving ligand selectivity often remains either an elusive or time-consuming endeavour. Cyclic peptides (CPs) occupy a key niche in ligand space, able to achieve high affinity and selectivity while retaining synthetic accessibility. De novo cyclic peptide ligands can be rapidly generated against a given target using mRNA display. In this study we harness mRNA display technology and the wealth of next generation sequencing (NGS) data generated to explore both experimental approaches and bioinformatic, statistical data analysis of peptide enrichment in cross-screen selections to rapidly generate high affinity CPs with differing intra-family protein selectivity profiles against fibroblast growth factor receptor (FGF-R) family proteins. Using these methods, CPs with distinct selectivity profiles can be generated which can serve as valuable tool compounds to decipher biological questions.

Latent functional diversity may accelerate microbial community responses to temperature fluctuations.

How complex microbial communities respond to climatic fluctuations remains an open question. Due to their relatively short generation times and high functional diversity, microbial populations harbor great potential to respond as a community through a combination of strain-level phenotypic plasticity, adaptation, and species sorting. However, the relative importance of these mechanisms remains unclear. We conducted a laboratory experiment to investigate the degree to which bacterial communities can respond to changes in environmental temperature through a combination of phenotypic plasticity and species sorting alone. We grew replicate soil communities from a single location at six temperatures between 4°C and 50°C. We found that phylogenetically and functionally distinct communities emerge at each of these temperatures, with K-strategist taxa favored under cooler conditions and r-strategist taxa under warmer conditions. We show that this dynamic emergence of distinct communities across a wide range of temperatures (in essence, community-level adaptation) is driven by the resuscitation of latent functional diversity: the parent community harbors multiple strains pre-adapted to different temperatures that are able to 'switch on' at their preferred temperature without immigration or adaptation. Our findings suggest that microbial community function in nature is likely to respond rapidly to climatic temperature fluctuations through shifts in species composition by resuscitation of latent functional diversity.

Most ecosystems on Earth rely on dynamic communities of microorganisms which help to cycle nutrients in the environment. There is increasing concern that climate change may have a profound impact on these complex networks formed of large numbers of microbial species linked by intricate biochemical relationships. Any species within a microbial community can acclimate to new temperatures by quickly tweaking their biological processes, for example by activating genes that are more suited to warmer conditions. Over time, a species may acclimate or adapt to new conditions. However, the community as a whole can also respond to these changes, and often much faster, by simply altering the abundance or presence of its members through a process known as species sorting. It remains unclear exactly how acclimation, adaptation and species sorting each contribute to the community's response to a temperature shift ­ an increasingly common scenario under global climate change. To address this question, Smith et al. investigated how species sorting and acclimation may help whole soil bacterial communities to cope with lasting changes in temperature. To do so, soil samples from a single field site (and therefore featuring the same microbial community) were incubated for four weeks under six different temperatures. Genetic analyses revealed that, at the end of the experiments, distinct communities specific to a given temperature had emerged. They all differed in species composition and the types of biological functions they could perform. Further experiments showed that each community had been taken over by strains of bacteria which grew best at the new temperature that they had been exposed to, including extreme warming scenarios never seen in their native environment. This suggests that these organisms were already present in the original community. They had persisted even under temperatures which were not optimal for them, acting as a slumbering ('latent') 'reservoir' of traits and functional abilities that allowed species sorting to produce distinct and functionally capable communities in each novel thermal environment. This suggests that species sorting could help bacterial communities to cope with dramatic changes in their thermal environment. Smith et al.'s findings suggest that bacterial communities can cope with warming environments much better than has been previously thought. In the future, this work may help researchers to better predict how climate change could impact microbial community structure and functioning, and most crucially their contributions to the global carbon cycle.

AREAdata: A worldwide climate dataset averaged across spatial units at different scales through time.

In an era of increasingly cross-discipline collaborative science, it is imperative to produce data resources which can be quickly and easily utilised by non-specialists. In particular, climate data often require heavy processing before they can be used for analyses. Here we describe AREAdata, a continually updated, free-to-use online global climate dataset, pre-processed to provide the averages of various climate variables across different administrative units (e.g., countries, states). These are daily estimates, based on the Copernicus Climate Data Store's ERA-5 data, regularly updated to the near-present and provided as direct downloads from our website (https://pearselab.github.io/areadata/). The daily climate estimates from AREAdata are consistent with other openly available data, but at much finer-grained spatial and temporal scales than available elsewhere. AREAdata complements the existing suite of climate resources by providing these data in a form more readily usable by researchers unfamiliar with GIS data-processing methods, and we anticipate these resources being of particular use to environmental and epidemiological researchers.

Cross-reactivity in assays for prolactin and optimum screening policy for macroprolactinaemia.

OBJECTIVES: Macroprolactin cross-reacts in immunoassays for prolactin causing apparent hyperprolactinaemia (macroprolactinaemia) and consequent misdiagnosis and mismanagement of patients. METHODS: We determined the prevalence of macroprolactinaemia using prolactin immunoassays with reported "high" (Tosoh) or "low" cross-reactivity (Roche) with macroprolactin. We additionally modelled the effects of increasing the screening threshold on workload and sensitivity in the detection of macroprolactinaemia. RESULTS: A review of routine requests for prolactin received in a 12 month period identified 670 sera with hyperprolactinaemia (Tosoh assay). Treatment with polyethylene glycol (PEG) precipitation demonstrated normal levels of monomeric prolactin in 165 sera (24.6%) indicating macroprolactinaemia. In the macroprolactinaemic cohort, total prolactin levels were lower with the Roche assay (473 ± 132 mU/L; mean ± SD) compared to the Tosoh assay (683 ± 217 mU/L), p < 0.005. The prevalence of macroprolactinaemia was also lower with the Roche assay (6.2%). The number of samples that required screening for macroprolactinaemia fell by 14% when Roche gender specific total prolactin reference limits were applied. Use of a higher screening threshold (700 mU/L) reduced the screening workload considerably (Roche by 45%, Tosoh by 37%) however, the sensitivity of detection of macroprolactinaemia decreased markedly (Roche 90%, Tosoh 59%). CONCLUSIONS: Macroprolactin interferes in both Tosoh and Roche prolactin immunoassays. Use of an assay with a relatively low cross reactivity with macroprolactin, e.g. Roche, will lead to a modest reduction in the screening workload. Increasing the screening threshold above the upper limit of the assay reference interval will also reduce the screening workload but leads to disproportionate increases in the number of cases of macroprolactinaemia which are missed.

Interference by macroprolactin in assays for prolactin: will the In Vitro Diagnostics Regulation lead to a solution at last?

Cross reactivity with high molecular weight complexes of prolactin known as macroprolactin is a common cause of positive interference in assays for serum prolactin. All prolactin assays currently available are affected with 5-25% of results indicating hyperprolactinaemia falsely elevated due to macroprolactinaemia - hyperprolactinaemia due to macroprolactin with normal concentrations of bioactive monomeric prolactin. Macroprolactinaemia has no pathological significance but, if it is not recognised as the cause, the apparent hyperprolactinaemia can lead to clinical confusion, unnecessary further investigations, inappropriate treatment and waste of healthcare resources. Macroprolactinaemia cannot be distinguished from true hyperprolactinaemia on clinical grounds alone but can be detected by a simple laboratory test based on the precipitation of macroprolactin with polyethylene glycol. Laboratory screening of all cases of hyperprolactinaemia to exclude macroprolactinaemia has been advised as best practice but has not been implemented universally and reports of clinical confusion caused by macroprolactinaemia continue to appear in the literature. Information provided by manufacturers to users of assays for prolactin regarding interference by macroprolactin is absent or inadequate and does not comply with the European Union Regulation covering in vitro diagnostic medical devices (IVDR). As the IVDR is implemented notified bodies should insist that manufacturers of assays for serum prolactin comply with the regulations by informing users that macroprolactin is a source of interference which may have untoward clinical consequences and by providing an estimate of the magnitude of the interference and a means of detecting macroprolactinaemia. Laboratories should institute a policy for excluding macroprolactinaemia in all cases of hyperprolactinaemia.

The role of competition versus cooperation in microbial community coalescence.

New microbial communities often arise through the mixing of two or more separately assembled parent communities, a phenomenon that has been termed "community coalescence". Understanding how the interaction structures of complex parent communities determine the outcomes of coalescence events is an important challenge. While recent work has begun to elucidate the role of competition in coalescence, that of cooperation, a key interaction type commonly seen in microbial communities, is still largely unknown. Here, using a general consumer-resource model, we study the combined effects of competitive and cooperative interactions on the outcomes of coalescence events. To do so, we simulate coalescence events between pairs of communities with different degrees of competition for shared carbon resources and cooperation through cross-feeding on leaked metabolic by-products (facilitation). We also study how structural and functional properties of post-coalescence communities evolve when they are subjected to repeated coalescence events. We find that in coalescence events, the less competitive and more cooperative parent communities contribute a higher proportion of species to the new community because of their superior ability to deplete resources and resist invasions. Consequently, when a community is subjected to repeated coalescence events, it gradually evolves towards being less competitive and more cooperative, as well as more speciose, robust and efficient in resource use. Encounters between microbial communities are becoming increasingly frequent as a result of anthropogenic environmental change, and there is great interest in how the coalescence of microbial communities affects environmental and human health. Our study provides new insights into the mechanisms behind microbial community coalescence, and a framework to predict outcomes based on the interaction structures of parent communities.

Systematic variation in the temperature dependence of bacterial carbon use efficiency.

Carbon use efficiency (CUE) is a key characteristic of microbial physiology and underlies community-level responses to changing environments. Yet, we currently lack general empirical insights into variation in microbial CUE at the level of individual taxa. Here, through experiments with 29 strains of environmentally isolated bacteria, we find that bacterial CUE typically responds either positively to temperature, or has no discernible response, within biologically meaningful temperature ranges. Using a global data synthesis, we show that these results are generalisable across most culturable groups of bacteria. This variation in the thermal responses of bacterial CUE is taxonomically structured, and stems from the fact that relative to respiration rates, bacterial population growth rates typically respond more strongly to temperature, and are also subject to weaker evolutionary constraints. Our results provide new insights into microbial physiology, and a basis for more accurately modelling the effects of thermal fluctuations on complex microbial communities.

Temperature and population density influence SARS-CoV-2 transmission in the absence of nonpharmaceutical interventions.

As COVID-19 continues to spread across the world, it is increasingly important to understand the factors that influence its transmission. Seasonal variation driven by responses to changing environment has been shown to affect the transmission intensity of several coronaviruses. However, the impact of the environment on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains largely unknown, and thus seasonal variation remains a source of uncertainty in forecasts of SARS-CoV-2 transmission. Here we address this issue by assessing the association of temperature, humidity, ultraviolet radiation, and population density with estimates of transmission rate (R). Using data from the United States, we explore correlates of transmission across US states using comparative regression and integrative epidemiological modeling. We find that policy intervention ("lockdown") and reductions in individuals' mobility are the major predictors of SARS-CoV-2 transmission rates, but, in their absence, lower temperatures and higher population densities are correlated with increased SARS-CoV-2 transmission. Our results show that summer weather cannot be considered a substitute for mitigation policies, but that lower autumn and winter temperatures may lead to an increase in transmission intensity in the absence of policy interventions or behavioral changes. We outline how this information may improve the forecasting of COVID-19, reveal its future seasonal dynamics, and inform intervention policies.

Toward a Point-of-Need Bioluminescence-Based Immunoassay Utilizing a Complete Shelf-Stable Reagent.

Enzyme-linked immunosorbent assays (ELISAs) are used extensively for the detection and quantification of biomolecules in clinical diagnostics as well as in basic research. Although broadly used, the inherent complexities of ELISAs preclude their utility for straightforward point-of-need testing, where speed and simplicity are essential. With this in mind, we developed a bioluminescence-based immunoassay format that provides a sensitive and simple method for detecting biomolecules in clinical samples. We utilized a ternary, split-NanoLuc luciferase complementation reporter consisting of two small peptides (11mer, 13mer) and a 17 kDa polypeptide combined with a luminogenic substrate to create a complete, shelf-stable add-and-read assay detection reagent. Directed evolution was used to optimize reporter constituent sequences to impart chemical and thermal stability, as well as solubility, while formulation optimization was applied to stabilize an all-in-one reagent that can be reconstituted in aqueous buffers or sample matrices. The result of these efforts is a robust, first-generation bioluminescence-based homogenous immunoassay reporter platform where all assay components can be configured into a stable lyophilized cake, supporting homogeneous, rapid, and sensitive one-step biomolecule quantification in complex human samples. This technology represents a promising alternative immunoassay format with significant potential to bring critical diagnostic molecular detection testing closer to the point-of-need.

Adaptive evolution shapes the present-day distribution of the thermal sensitivity of population growth rate.

Developing a thorough understanding of how ectotherm physiology adapts to different thermal environments is of crucial importance, especially in the face of global climate change. A key aspect of an organism's thermal performance curve (TPC)-the relationship between fitness-related trait performance and temperature-is its thermal sensitivity, i.e., the rate at which trait values increase with temperature within its typically experienced thermal range. For a given trait, the distribution of thermal sensitivities across species, often quantified as "activation energy" values, is typically right-skewed. Currently, the mechanisms that generate this distribution are unclear, with considerable debate about the role of thermodynamic constraints versus adaptive evolution. Here, using a phylogenetic comparative approach, we study the evolution of the thermal sensitivity of population growth rate across phytoplankton (Cyanobacteria and eukaryotic microalgae) and prokaryotes (bacteria and archaea), 2 microbial groups that play a major role in the global carbon cycle. We find that thermal sensitivity across these groups is moderately phylogenetically heritable, and that its distribution is shaped by repeated evolutionary convergence throughout its parameter space. More precisely, we detect bursts of adaptive evolution in thermal sensitivity, increasing the amount of overlap among its distributions in different clades. We obtain qualitatively similar results from evolutionary analyses of the thermal sensitivities of 2 physiological rates underlying growth rate: net photosynthesis and respiration of plants. Furthermore, we find that these episodes of evolutionary convergence are consistent with 2 opposing forces: decrease in thermal sensitivity due to environmental fluctuations and increase due to adaptation to stable environments. Overall, our results indicate that adaptation can lead to large and relatively rapid shifts in thermal sensitivity, especially in microbes for which rapid evolution can occur at short timescales. Thus, more attention needs to be paid to elucidating the implications of rapid evolution in organismal thermal sensitivity for ecosystem functioning.

NanoBiT System and Hydrofurimazine for Optimized Detection of Viral Infection in Mice-A Novel in Vivo Imaging Platform.

Reporter genes are used to visualize intracellular biological phenomena, including viral infection. Here we demonstrate bioluminescent imaging of viral infection using the NanoBiT system in combination with intraperitoneal injection of a furimazine analogue, hydrofurimazine. This recently developed substrate has enhanced aqueous solubility allowing delivery of higher doses for in vivo imaging. The small high-affinity peptide tag (HiBiT), which is only 11 amino-acids in length, was engineered into a clinically used oncolytic adenovirus, and the complementary large protein (LgBiT) was constitutively expressed in tumor cells. Infection of the LgBiT expressing cells with the HiBiT oncolytic virus will reconstitute NanoLuc in the cytosol of the cell, providing strong bioluminescence upon treatment with substrate. This new bioluminescent system served as an early stage quantitative viral transduction reporter in vitro and also in vivo in mice, for longitudinal monitoring of oncolytic viral persistence in infected tumor cells. This platform provides novel opportunities for studying the biology of viruses in animal models.

Novel NanoLuc substrates enable bright two-population bioluminescence imaging in animals.

Sensitive detection of two biological events in vivo has long been a goal in bioluminescence imaging. Antares, a fusion of the luciferase NanoLuc to the orange fluorescent protein CyOFP, has emerged as a bright bioluminescent reporter with orthogonal substrate specificity to firefly luciferase (FLuc) and its derivatives such as AkaLuc. However, the brightness of Antares in mice is limited by the poor solubility and bioavailability of the NanoLuc substrate furimazine. Here, we report a new substrate, hydrofurimazine, whose enhanced aqueous solubility allows delivery of higher doses to mice. In the liver, Antares with hydrofurimazine exhibited similar brightness to AkaLuc with its substrate AkaLumine. Further chemical exploration generated a second substrate, fluorofurimazine, with even higher brightness in vivo. We used Antares with fluorofurimazine to track tumor size and AkaLuc with AkaLumine to visualize CAR-T cells within the same mice, demonstrating the ability to perform two-population imaging with these two luciferase systems.

Community-level respiration of prokaryotic microbes may rise with global warming.

Understanding how the metabolic rates of prokaryotes respond to temperature is fundamental to our understanding of how ecosystem functioning will be altered by climate change, as these micro-organisms are major contributors to global carbon efflux. Ecological metabolic theory suggests that species living at higher temperatures evolve higher growth rates than those in cooler niches due to thermodynamic constraints. Here, using a global prokaryotic dataset, we find that maximal growth rate at thermal optimum increases with temperature for mesophiles (temperature optima [Formula: see text]C), but not thermophiles ([Formula: see text]C). Furthermore, short-term (within-day) thermal responses of prokaryotic metabolic rates are typically more sensitive to warming than those of eukaryotes. Because climatic warming will mostly impact ecosystems in the mesophilic temperature range, we conclude that as microbial communities adapt to higher temperatures, their metabolic rates and therefore, biomass-specific CO[Formula: see text] production, will inevitably rise. Using a mathematical model, we illustrate the potential global impacts of these findings.

Ecological speciation in sympatric palms: 4. Demographic analyses support speciation of Howea in the face of high gene flow.

The idea that populations must be geographically isolated (allopatric) to evolve into separate species has persisted for a long time. It is now clear that new species can also diverge despite ongoing genetic exchange, but few accepted cases of speciation in sympatry have held up when scrutinized using modern approaches. Here, we examined evidence for speciation of the Howea palms of Lord Howe Island, Australia, in light of new genomic data. We used coalescence-based demographic models combined with double digest restriction site associated DNA sequencing of multiple individuals and provide support for previous claims by Savolainen et al. that speciation in Howea did occur in the face of gene flow.

Comparative genomics of bdelloid rotifers: Insights from desiccating and nondesiccating species.

Bdelloid rotifers are a class of microscopic invertebrates that have existed for millions of years apparently without sex or meiosis. They inhabit a variety of temporary and permanent freshwater habitats globally, and many species are remarkably tolerant of desiccation. Bdelloids offer an opportunity to better understand the evolution of sex and recombination, but previous work has emphasised desiccation as the cause of several unusual genomic features in this group. Here, we present high-quality whole-genome sequences of 3 bdelloid species: Rotaria macrura and R. magnacalcarata, which are both desiccation intolerant, and Adineta ricciae, which is desiccation tolerant. In combination with the published assembly of A. vaga, which is also desiccation tolerant, we apply a comparative genomics approach to evaluate the potential effects of desiccation tolerance and asexuality on genome evolution in bdelloids. We find that ancestral tetraploidy is conserved among all 4 bdelloid species, but homologous divergence in obligately aquatic Rotaria genomes is unexpectedly low. This finding is contrary to current models regarding the role of desiccation in shaping bdelloid genomes. In addition, we find that homologous regions in A. ricciae are largely collinear and do not form palindromic repeats as observed in the published A. vaga assembly. Consequently, several features interpreted as genomic evidence for long-term ameiotic evolution are not general to all bdelloid species, even within the same genus. Finally, we substantiate previous findings of high levels of horizontally transferred nonmetazoan genes in both desiccating and nondesiccating bdelloid species and show that this unusual feature is not shared by other animal phyla, even those with desiccation-tolerant representatives. These comparisons call into question the proposed role of desiccation in mediating horizontal genetic transfer.

Use and misuse of temperature normalisation in meta-analyses of thermal responses of biological traits.

There is currently unprecedented interest in quantifying variation in thermal physiology among organisms, especially in order to understand and predict the biological impacts of climate change. A key parameter in this quantification of thermal physiology is the performance or value of a rate, across individuals or species, at a common temperature (temperature normalisation). An increasingly popular model for fitting thermal performance curves to data-the Sharpe-Schoolfield equation-can yield strongly inflated estimates of temperature-normalised rate values. These deviations occur whenever a key thermodynamic assumption of the model is violated, i.e., when the enzyme governing the performance of the rate is not fully functional at the chosen reference temperature. Using data on 1,758 thermal performance curves across a wide range of species, we identify the conditions that exacerbate this inflation. We then demonstrate that these biases can compromise tests to detect metabolic cold adaptation, which requires comparison of fitness or rate performance of different species or genotypes at some fixed low temperature. Finally, we suggest alternative methods for obtaining unbiased estimates of temperature-normalised rate values for meta-analyses of thermal performance across species in climate change impact studies.