Microbial tropicalization driven by a strengthening western ocean boundary current

Western boundary currents (WBCs) redistribute heat and oligotrophic seawater from the tropics to temperate latitudes, with several displaying substantial climate change‐driven intensification over the last century. Strengthening WBCs have been implicated in the poleward range expansion of marine macroflora and fauna, however, the impacts on the structure and function of temperate microbial communities are largely unknown. Here we show that the major subtropical WBC of the South Pacific Ocean, the East Australian Current (EAC), transports microbial assemblages that maintain tropical and oligotrophic (k‐strategist) signatures, to seasonally displace more copiotrophic (r‐strategist) temperate microbial populations within temperate latitudes of the Tasman Sea. We identified specific characteristics of EAC microbial assemblages compared with non‐EAC assemblages, including strain transitions within the SAR11 clade, enrichment of Prochlorococcus, predicted smaller genome sizes and shifts in the importance of several functional genes, including those associated with cyanobacterial photosynthesis, secondary metabolism and fatty acid and lipid transport. At a temperate time‐series site in the Tasman Sea, we observed significant reductions in standing stocks of total carbon and chlorophyll a, and a shift towards smaller phytoplankton and carnivorous copepods, associated with the seasonal impact of the EAC microbial assemblage. In light of the substantial shifts in microbial assemblage structure and function associated with the EAC, we conclude that climate‐driven expansions of WBCs will expand the range of tropical oligotrophic microbes, and potentially profoundly impact the trophic status of temperate waters.     

Disentangling the potential effects of land‐use and climate change on stream conditions

Land‐use and climate change are significantly affecting stream ecosystems, yet understanding of their long‐term impacts is hindered by the few studies that have simultaneously investigated their interaction and high variability among future projections. We modeled possible effects of a suite of 2030, 2060, and 2090 land‐use and climate scenarios on the condition of 70,772 small streams in the Chesapeake Bay watershed, United States. The Chesapeake Basin‐wide Index of Biotic Integrity, a benthic macroinvertebrate multimetric index, was used to represent stream condition. Land‐use scenarios included four Special Report on Emissions Scenarios (A1B, A2, B1, and B2) representing a range of potential landscape futures. Future climate scenarios included quartiles of future climate changes from downscaled Coupled Model Intercomparison Project ‐ Phase 5 (CMIP5) and a watershed‐wide uniform scenario (Lynch2016). We employed random forests analysis to model individual and combined effects of land‐use and climate change on stream conditions. Individual scenarios suggest that by 2090, watershed‐wide conditions may exhibit anywhere from large degradations (e.g., scenarios A1B, A2, and the CMIP5 25th percentile) to small degradations (e.g., scenarios B1, B2, and Lynch2016). Combined land‐use and climate change scenarios highlighted their interaction and predicted, by 2090, watershed‐wide degradation in 16.2% (A2 CMIP5 25th percentile) to 1.0% (B2 Lynch2016) of stream kilometers. A goal for the Chesapeake Bay watershed is to restore 10% of stream kilometers over a 2008 baseline; our results suggest meeting and sustaining this goal until 2090 may require improvement in 11.0%–26.2% of stream kilometers, dependent on land‐use and climate scenario. These results highlight inherent variability among scenarios and the resultant uncertainty of predicted conditions, which reinforces the need to incorporate multiple scenarios of both land‐use (e.g., development, agriculture, etc.) and climate change in future studies to encapsulate the range of potential future conditions.     

Population modelling and genetics of a critically endangered Madagascan palm Tahina spectabilis

Madagascar is home to 208 indigenous palm species, almost all of them endemic and >80% of which are endangered. We undertook complete population census and sampling for genetic analysis of a relatively recently discovered giant fan palm, the Critically Endangered Tahina spectablis in 2008 and 2016. Our 2016 study included newly discovered populations and added to our genetic study. We incorporated these new populations into species distribution niche model (SDM) and projected these onto maps of the region. We developed population matrix models based on observed demographic data to model population change and predict the species vulnerability to extinction by undertaking population viability analysis (PVA). We investigated the potential conservation value of reintroduced planted populations within the species potential suitable habitat. We found that the population studied in 2008 had grown in size due to seedling regeneration but had declined in the number of reproductively mature plants, and we were able to estimate that the species reproduces and dies after approximately 70 years. Our models suggest that if the habitat where it resides continues to be protected the species is unlikely to go extinct due to inherent population decline and that it will likely experience significant population growth after approximately 80 years due to the reproductive and life cycle attributes of the species. The newly discovered populations contain more genetic diversity than the first discovered southern population which is genetically depauperate. The species appears to demonstrate a pattern of dispersal leading to isolated founder plants which may eventually lead to population development depending on local establishment opportunities. The conservation efforts currently put in place including the reintroduction of plants within the species potential suitable habitat if maintained are thought likely to enable the species to sustain itself but it remains vulnerable to anthropogenic impacts.     

Acoustic localization of terrestrial wildlife: Current practices and future opportunities

Autonomous acoustic recorders are an increasingly popular method for low‐disturbance, large‐scale monitoring of sound‐producing animals, such as birds, anurans, bats, and other mammals. A specialized use of autonomous recording units (ARUs) is acoustic localization, in which a vocalizing animal is located spatially, usually by quantifying the time delay of arrival of its sound at an array of time‐synchronized microphones. To describe trends in the literature, identify considerations for field biologists who wish to use these systems, and suggest advancements that will improve the field of acoustic localization, we comprehensively review published applications of wildlife localization in terrestrial environments. We describe the wide variety of methods used to complete the five steps of acoustic localization: (1) define the research question, (2) obtain or build a time‐synchronizing microphone array, (3) deploy the array to record sounds in the field, (4) process recordings captured in the field, and (5) determine animal location using position estimation algorithms. We find eight general purposes in ecology and animal behavior for localization systems: assessing individual animals' positions or movements, localizing multiple individuals simultaneously to study their interactions, determining animals' individual identities, quantifying sound amplitude or directionality, selecting subsets of sounds for further acoustic analysis, calculating species abundance, inferring territory boundaries or habitat use, and separating animal sounds from background noise to improve species classification. We find that the labor‐intensive steps of processing recordings and estimating animal positions have not yet been automated. In the near future, we expect that increased availability of recording hardware, development of automated and open‐source localization software, and improvement of automated sound classification algorithms will broaden the use of acoustic localization. With these three advances, ecologists will be better able to embrace acoustic localization, enabling low‐disturbance, large‐scale collection of animal position data.     

One size does not fit all: Customizing MCMC methods for hierarchical models using NIMBLE

Improved efficiency of Markov chain Monte Carlo facilitates all aspects of statistical analysis with Bayesian hierarchical models. Identifying strategies to improve MCMC performance is becoming increasingly crucial as the complexity of models, and the run times to fit them, increases. We evaluate different strategies for improving MCMC efficiency using the open‐source software NIMBLE (R package nimble) using common ecological models of species occurrence and abundance as examples. We ask how MCMC efficiency depends on model formulation, model size, data, and sampling strategy. For multiseason and/or multispecies occupancy models and for N‐mixture models, we compare the efficiency of sampling discrete latent states vs. integrating over them, including more vs. fewer hierarchical model components, and univariate vs. block‐sampling methods. We include the common MCMC tool JAGS in comparisons. For simple models, there is little practical difference between computational approaches. As model complexity increases, there are strong interactions between model formulation and sampling strategy on MCMC efficiency. There is no one‐size‐fits‐all best strategy, but rather problem‐specific best strategies related to model structure and type. In all but the simplest cases, NIMBLE's default or customized performance achieves much higher efficiency than JAGS. In the two most complex examples, NIMBLE was 10–12 times more efficient than JAGS. We find NIMBLE is a valuable tool for many ecologists utilizing Bayesian inference, particularly for complex models where JAGS is prohibitively slow. Our results highlight the need for more guidelines and customizable approaches to fit hierarchical models to ensure practitioners can make the most of occupancy and other hierarchical models. By implementing model‐generic MCMC procedures in open‐source software, including the NIMBLE extensions for integrating over latent states (implemented in the R package nimbleEcology), we have made progress toward this aim.     

RNAi‐mediated Ultra‐low gossypol cottonseed trait: performance of transgenic lines under field conditions

Cottonseed remains a low‐value by‐product of lint production mainly due to the presence of toxic gossypol that makes it unfit for monogastrics. Ultra‐low gossypol cottonseed (ULGCS) lines were developed using RNAi knockdown of δ‐cadinene synthase gene(s) in Gossypium hirsutum. The purpose of the current study was to assess the stability and specificity of the ULGCS trait and evaluate the agronomic performance of the transgenic lines. Trials conducted over a period of 3 years show that the ULGCS trait was stable under field conditions and the foliage/floral organs of transgenic lines contained wild‐type levels of gossypol and related terpenoids. Although it was a relatively small‐scale study, we did not observe any negative effects on either the yield or quality of the fibre and seed in the transgenic lines compared with the nontransgenic parental plants. Compositional analysis was performed on the seeds obtained from plants grown in the field during 2009. As expected, the major difference between the ULGCS and wild‐type cottonseeds was in terms of their gossypol levels. With the exception of oil content, the composition of ULGCS was similar to that of nontransgenic cottonseeds. Interestingly, the ULGCS had significantly higher (4%–8%) oil content compared with the seeds from the nontransgenic parent. Field trial results confirmed the stability and specificity of the ULGCS trait suggesting that this RNAi‐based product has the potential to be commercially viable. Thus, it may be possible to enhance and expand the nutritional utility of the annual cottonseed output to fulfil the ever‐increasing needs of humanity.     

Profiles of Serum Cytokines in Acute Drug-Induced Liver Injury and Their Prognostic Significance

Drug-induced liver injury (DILI) is the most common cause of acute liver failure in the United-States. The aim of the study was to describe serum immune profiles associated with acute DILI, to investigate whether there are profiles associated with clinical features or types of DILI and/or with prognosis, and to assess temporal changes in levels. Twenty-seven immune analytes were measured in the sera of 78 DILI subjects in the Drug-Induced Liver Injury Network (DILIN) and compared with 40 healthy controls. Immune analytes (14 cytokines, 7 chemokines and 6 growth factors) were measured by BioPlex multiplex ELISA at DILI onset and after 6 months. A modeling process utilizing immune principles was used to select a final set of variables among 27 immune analytes and several additional clinical lab values for prediction of early death (within 6 months of DILI onset). Nineteen of the 27 immune analytes were differentially expressed among healthy control, DILI onset and 6-month cohorts. Disparate patterns of immune responses, especially innate and adaptive cellular (mostly TH17) immunity were evident. Low values of four immune analytes (IL-9, IL-17, PDGF-bb and RANTES) and serum albumin are predictive of early death [PPV = 88% (95% CI, 65%-100%), NPV = 97% (95% CI, 93%-100%), accuracy = 96% (95% CI, 92%-100%)].

Conclusions

Acute DILI is associated with robust and varying immune responses. High levels of expression of cytokines associated with innate immunity are associated with a poor prognosis, whereas high levels of expression of adaptive cytokines are associated with good long-term prognosis and eventual recovery. Serum immune analyte profiles at DILI onset appear to be of prognostic, and perhaps, diagnostic significance.     

Application of Multiplexed Kinase Inhibitor Beads to Study Kinome Adaptations in Drug-Resistant Leukemia

Protein kinases play key roles in oncogenic signaling and are a major focus in the development of targeted cancer therapies. Imatinib, a BCR-Abl tyrosine kinase inhibitor, is a successful front-line treatment for chronic myelogenous leukemia (CML). However, resistance to imatinib may be acquired by BCR-Abl mutations or hyperactivation of Src family kinases such as Lyn. We have used multiplexed kinase inhibitor beads (MIBs) and quantitative mass spectrometry (MS) to compare kinase expression and activity in an imatinib-resistant (MYL-R) and -sensitive (MYL) cell model of CML. Using MIB/MS, expression and activity changes of over 150 kinases were quantitatively measured from various protein kinase families. Statistical analysis of experimental replicates assigned significance to 35 of these kinases, referred to as the MYL-R kinome profile. MIB/MS and immunoblotting confirmed the over-expression and activation of Lyn in MYL-R cells and identified additional kinases with increased (MEK, ERK, IKKα, PKCβ, NEK9) or decreased (Abl, Kit, JNK, ATM, Yes) abundance or activity. Inhibiting Lyn with dasatinib or by shRNA-mediated knockdown reduced the phosphorylation of MEK and IKKα. Because MYL-R cells showed elevated NF-κB signaling relative to MYL cells, as demonstrated by increased IκBα and IL-6 mRNA expression, we tested the effects of an IKK inhibitor (BAY 65-1942). MIB/MS and immunoblotting revealed that BAY 65-1942 increased MEK/ERK signaling and that this increase was prevented by co-treatment with a MEK inhibitor (AZD6244). Furthermore, the combined inhibition of MEK and IKKα resulted in reduced IL-6 mRNA expression, synergistic loss of cell viability and increased apoptosis. Thus, MIB/MS analysis identified MEK and IKKα as important downstream targets of Lyn, suggesting that co-targeting these kinases may provide a unique strategy to inhibit Lyn-dependent imatinib-resistant CML. These results demonstrate the utility of MIB/MS as a tool to identify dysregulated kinases and to interrogate kinome dynamics as cells respond to targeted kinase inhibition.     

In Vitro Formation of β Cell Pseudoislets Using Islet-Derived Endothelial Cells

β cell pseudoislets (PIs) are used for the in vitro study of β-cells in a three-dimensional (3-D) configuration. Current methods of PI induction require unique culture conditions and extensive mechanical manipulations. Here we report a novel co-culture system consisting of high passage β-cells and islet-derived endothelial cells (iECs) that results in a rapid and spontaneous formation of free-floating PIs. PI structures were formed as early as 72 h following co-culture setup and were preserved for more than 14 d. These PIs, composed solely of β-cells, were similar in size to that of native islets and showed an increased percentage of proinsulin-positive cells, increased insulin gene expression in response to glucose stimulation, and restored glucose-stimulated insulin secretion when compared to β-cells cultured as monolayers. Key extracellular matrix proteins that were absent in β-cells cultured alone were deposited by iECs on PIs and were found in and around the PIs. iEC-induced PIs are a readily available tool for examining β cell function in a native 3-D configuration and can be used for examining β-cell/iEC interactions in vitro.