title: Using Deep Learning for Gene Detection and Classification in Raw Nanopore Signals

abstract: Recently, nanopore sequencing has come to the fore as library preparation is rapid and simple, sequencing can be done almost anywhere, and longer reads are obtained than with next-generation sequencing. The main bottleneck still lies in data postprocessing which consists of basecalling, genome assembly, and localizing significant sequences, which is time consuming and computationally demanding, thus prolonging delivery of crucial results for clinical practice. Here, we present a neural network-based method capable of detecting and classifying specific genomic regions already in raw nanopore signals - squiggles. Therefore, the basecalling process can be omitted entirely as the raw signals of significant genes, or intergenic regions can be directly analysed, or if the nucleotide sequences are required, the identified squiggles can be basecalled, preferably to others. The proposed neural network could be included directly in the sequencing run, allowing real-time squiggle processing.

category: bioinformatics


title: binny: an automated binning algorithm to recover high-quality genomes from complex metagenomic datasets

abstract:
The reconstruction of genomes is a critical step in genome-resolved metagenomics as well as for multi-omic data integration from microbial communities. Here, we present binny, a binning tool that produces high-quality metagenome-assembled genomes from both contiguous and highly fragmented genomes. Based on established metrics, binny outperforms existing state-of-the-art binning methods and finds unique genomes that could not be detected by other methods.

binny uses k-mer-composition and coverage by metagenomic reads for iterative, non-linear dimension reduction of genomic signatures as well as subsequent automated contig clustering with cluster assessment using lineage-specific marker gene sets.

When compared to five widely used binning algorithms, binny recovers the most near-complete (>95% pure, >90% complete) and high-quality (>90% pure, >70% complete) genomes from simulated data sets from the Critical Assessment of Metagenome Interpretation (CAMI) initiative, as well as from a real-world benchmark comprised of metagenomes from various environments. binny is implemented as Snakemake workflow and available from https://github.com/a-h-b/binny.


title: A guide to trajectory inference and RNA velocity

abstract: Technological developments have led to an explosion of high-throughput single cell data, which are revealing unprecedented perspectives on cell identity. Recently, significant attention has focused on investigating, from single-cell RNA-sequencing (scRNA-seq) data, cellular dynamic processes, such as cell differentiation, cell cycle and cell (de)activation. Trajectory inference methods estimate a trajectory, a collection of differentiation paths of a dynamic system, by ordering cells along the paths of such a dynamic process. While trajectory inference tools typically work with gene expression levels, common scRNA-seq protocols allow the identification and quantification of unspliced pre-mRNAs and mature spliced mRNAs, for each gene. By exploiting the abundance of unspliced and spliced mRNA, one can infer the RNA velocity of individual cells, i.e., the time derivative of the gene expression state of cells. Whereas traditional trajectory inference methods reconstruct cellular dynamics given a population of cells of varying maturity, RNA velocity relies on a dynamical model describing splicing dynamics. Here, we initially discuss conceptual and theoretical aspects of both approaches, then illustrate how they can be combined together, and finally present an example use-case on real data.


title: Function-guided protein design by deep manifold sampling

abstract: Protein design is challenging because it requires searching through a vast combinatorial space that is only sparsely functional. Self-supervised learning approaches offer the potential to navigate through this space more effectively and thereby accelerate protein engineering. We introduce a sequence denoising autoencoder (DAE) that learns the manifold of protein sequences from a large amount of potentially unlabelled proteins. This DAE is combined with a function predictor that guides sampling towards sequences with higher levels of desired functions. We train the sequence DAE on more than 20M unlabeled protein sequences spanning many evolutionarily diverse protein families and train the function predictor on approximately 0.5M sequences with known function labels. At test time, we sample from the model by iteratively denoising a sequence while exploiting the gradients from the function predictor. We present a few preliminary case studies of protein design that demonstrate the effectiveness of this proposed approach, which we refer to as "deep manifold sampling", including metal binding site addition, function-preserving diversification, and global fold change.


title: Bridging functional annotation gaps in non-model plant genes with AlphaFold, DeepFRI and small molecule docking

abstract:
BackgroundFunctional annotation assigns descriptive biological meaning to genetic sequences. Limited availability of manually curated or experimentally validated plant genes from a diverse range of taxa poses a significant challenge for functional annotation in non-model organisms. Accurate computational approaches are required. We argue that recent breakthroughs in deep learning have the potential to not only narrow the functional annotation gap between non-model and model plant organisms, but also annotate and reveal novel functions even for genes with no homologs in public databases.

ResultsDeep learning models were applied to functionally annotate a set of previously published differentially expressed genes. Predicted protein structures and functional annotations were generated using the AlphaFold protein structure and DeepFRI protein language inference models respectively. The resulting structures and functional annotations were validated using small molecule docking experiments. DeepFRI and AlphaFold models not only correctly annotated differentially expressed genes, but also revealed detailed mechanisms involving protein-protein interactions.

ConclusionsDeep learning models are capable of inferring novel functions and achieving high accuracy in functional annotation. Their increased use in plant research will result in major improvements in annotations for non-model plants that are underrepresented in genome databases. We illustrate how integrating protein structure prediction, functional residue prediction, and small molecule docking can infer plausible protein-protein interactions and yield additional mechanistic insights. This approach will aid in the selection of candidate genes for further study from differential expression studies that generate large gene lists.


title: Fast Medical Image Auto-segmentation for Bleeding Gastric Tissue Detection based on Deep DuS-KFCM Clustering

abstract:
BackgroundDetection and classification of gastric bleeding tissues are one of the challenging tasks in endoscopy image analysis. Lesion detection plays an important role in gastric cancer (GC) diagnosis and follow-up. Manual segmentation of endoscopy images is a very time-consuming task and subject to intra- and interrater variability. Accurate GB segmentation in abdominal sequences is an essential and crucial task for surgical planning and navigation in gastric lesion ablation. However, GB segmentation in endoscope is a substantially challenging work because the intensity values of gastric blood are similar to those of adjacent structures.

ObjectiveIn this paper the idea is to combine two parts: Neural Network and Fuzzy Logic--Hybrid Neuro-Fuzzy system. The objective of this manuscript is to provide an efficient way to segment the gastric bleeding lesion area. This work focuses on design and development of an automated diagnostic system using gastric bleeding cancer endoscopy images.

MethodsIn this paper, a coarse-to-fine method was applied to segment gastric bleeding lesion from endoscopy images, which consists of two stages including rough segmentation and refined segmentation. The rough segmentation is based on a kernel fuzzy C-means algorithm with spatial information (SKFCM) algorithm combined with spatial gray level co-occurrence matrix (GLCM) and the refined segmentation is implemented with deeplabv3+ (backbone with resnet50) algorithm to improve the overall accuracy.

ResultsExperimental results for gastric bleeding segmentation show that the method provides an accuracy of 87.9476% with specificity of 96.3343% and performs better than other related methods.

onclusionsThe performance of the method was evaluated using two benchmark datasets: The GB Segmentation and the healthy datasets. Then use the gastric red spots (GRS) dataset to do the final test to verify weak bleeding symptoms. Our method achieves high accuracy in gastric bleeding lesion segmentation. The work describes an innovative way of using GLCM based textural features to extract underlying information in gastric bleeding cancer imagery. Modified deep DuS-KFCM endoscopy image segmentation method based on GLCM feature, The experimental results shown to be effective in image segmentation and has good performance of resisting noise, segmentation effect more ideal.


title: The impact of low input DNA on the reliability of DNA methylation as measured by the Illumina Infinium MethylationEPIC BeadChip

abstract:
BackgroundDNA methylation (DNAm) is commonly assayed using the Illumina Infinium MethylationEPIC BeadChip, but there is currently little published evidence to define the lower limits of the amount of DNA that can be used whilst preserving data quality. Such evidence is valuable for analyses utilising precious or limited DNA sources.

Materials and methodsWe use a single pooled sample of DNA in quadruplicate at three dilutions to define replicability and noise, and an independent population dataset of 328 individuals (from a community-based study including US-born non-Hispanic Black and white persons) to assess the impact of total DNA input on the quality of data generated using the Illumina Infinium MethylationEPIC BeadChip.

ResultsData are less reliable and more noisy as DNA input decreases to 40ng, with clear reductions in data quality; however samples with a total input as low as 40ng pass standard quality control tests, and we observe little evidence that low input DNA obscures the associations between DNAm and two phenotypes, age and smoking status.

ConclusionsDNA input as low as 40ng can be used with the Illumina Infinium MethylationEPIC BeadChip, provided quality checks and sensitivity analyses are undertaken.


title: Phenotyping Polarization Dynamics Of Immune Cells Using A Lipid Droplet - Cell Pairing Microfluidic Platform

abstract:
The immune synapse is the tight contact zone between a lymphocyte and a cell presenting its cognate antigen. This structure serves as a signaling platform and entails a polarization of intra-cellular components, necessary to the immunological function of the cell. While the surface properties of the presenting cell are known to control the formation of the synapse, their impact on polarization has not yet been studied.

Using functional lipid droplets as tunable artificial presenting cells combined with a microfluidic pairing device, we simultaneously observe synchronized synapses and dynamically quantify polarization patterns of individual B cells. By assessing how the ligand concentration, the surface fluidity and the substrate rigidity impact this polarization, we show that its onset depends on the antigen concentration at the synapse, and that the substrate rigidity controls both its onset and its kinetics. Our experimental system enables a fine phenotyping of monoclonal cell populations based on their synaptic readout.

Significance statementTo fulfill their immune function, B cells acquire antigens presented on the surface of antigen-presenting cells and organize their cytoskeleton and lysosomal traffic towards the contact. The polarization mechanism is evolutionary conserved, making the system interesting both from the immunology and the cell biology point of view. We developed and finely characterized antigen-coated droplets as surrogate presenting cells with a physiological-flow microfluidic cell-pairing chip to explore the B cell lysosome polarization in response to changes in droplet mechanics and antigen concentration. We observed that polarization is sensitive to mechanical properties (responding more strongly but less fast on stiffer substrates) and to the local antigen concentration at the contact. Hence, surprisingly, a late cell response is sensitive to the mechanics of the contact.

category: biophysics


title: Onset and kinetics of B cell polarization depend on substrate mechanics and antigen concentration


title: A spectral demixing method for high-precision multi-color localization microscopy

abstract: Single molecule localization microscopy (SMLM) with a dichroic image splitter can provide invaluable multi-color information regarding colocalization of individual molecules, but it often suffers from technical limitations. So far, demixing algorithms give suboptimal results in terms of localization precision and correction of chromatic aberrations. Here we present an image splitter based multi-color SMLM method (splitSMLM) that offers much improved localization precision & drift correction, compensation of chromatic aberrations, and optimized performance of fluorophores in a specific buffer to equalize their reactivation rates for simultaneous imaging. A novel spectral demixing algorithm, SplitViSu, fully preserves localization precision with essentially no data loss and corrects chromatic aberrations at the nanometer scale. Multi-color performance is further improved by using optimized fluorophore and filter combinations. Applied to three-color imaging of the nuclear pore complex (NPC), this method provides a refined positioning of the individual NPC proteins and reveals that Pom121 clusters act as NPC deposition loci, hence illustrating strength and general applicability of the method.


title: A rhythmically pulsing leaf-spring nanoengine that drives a passive follower

abstract: Molecular engineering seeks to create functional entities for the modular use in the bottom-up design of nanoassemblies that can perform complex tasks. Such systems require fuel-consuming nanomotors that can actively drive downstream passive followers. Most molecular motors are driven by Brownian motion, but the generated forces are scattered and insufficient for efficient transfer to passive second-tier components, which is why nanoscale driver-follower systems have not been realized. Here, we describe bottom-up construction of a DNA-nanomachine that engages in an active, autonomous and rhythmical pulsing motion of two rigid DNA-origami arms, driven by chemical energy. We show the straightforward coupling of the active nanomachine to a passive follower unit, to which it then transmits its own motion, thus constituting a genuine driver-follower pair. Our work introduces a versatile fuel-consuming nanomachine that can be coupled with passive modules in nanoassemblies, the function of which depends on downstream sequences of motion.


title: A multi-state dynamical process underpins mechano-adaptation in the bacterial flagellar motor

abstract: Adaptation is a defining feature of living systems. The bacterial flagellar motor adapts to changes in the external mechanical environment by adding or removing torque-generating stator units. However, the molecular mechanism for mechanosensitive motor remodeling remains unclear. Here, we induced stator disassembly using electrorotation, followed by the time-dependent assembly of the individual stator units into the motor after electrorotation was terminated. From these experiments, we extracted detailed statistics of the dwell times that comprise the stochastic dynamics of the binding and unbinding of stator units. Dwell times reveal multiple timescales, indicating the existence of multiple binding states of the stator units. Based on these results, we propose a minimal model in which the stator unit can occupy four different states - two bound states with very different rates of unbinding, a diffusive unbound state, and a transiently detached state. Our minimal model quantitatively explains multiple features of the experimental data and allows us to determine the transition rates among all four states. Our experiments and modeling suggest a mechanism of mechano-adaptive remodeling of the bacterial flagellar motor in which torque generated by bound stator units controls their effective unbinding rate by modulating the transition between the two bound states. Furthermore, the binding rate of stator units with the motor has a non-monotonic dependence on the number of bound units, likely because of two counteracting effects of motor rotation on the binding process.


title: A multi-state dynamic process confers mechano-adaptation to the bacterial flagellar motor


title: A Lattice Model on the Rate of DNA Hybridization

abstract: We develop a lattice model on the rate of hybridization of the complementary single-stranded DNAs (c-ssDNAs). Upon translational diffusion mediated collisions, c-ssDNAs interpenetrate each other to form correct (cc), incorrect (icc) and trap-correct contacts (tcc) inside the reaction volume. Correct contacts are those with exact registry matches which leads to nucleation and zipping. Incorrect contacts are the mismatch contacts which are less stable compared to tcc which can occur in the repetitive c-ssDNAs. Although tcc possess registry match within the repeating sequences, they are incorrect contacts in the view of the whole c-ssDNAs. The nucleation rate (kN) is directly proportional to the collision rate and the average number of correct-contacts (<ncc>) formed when both the c-ssDNAs interpenetrate each other. Detailed lattice model simulations suggest that [<]ncc[>] {propto} L/V where L is the length of c-ssDNAs and V is the reaction volume. Further numerical analysis revealed the scaling for the average radius of gyration of c-ssDNAs (Rg) with their length as [Formula]. Since the reaction space will be approximately a sphere with radius equals to 2Rg and V {propto} L3/2, one obtains [Formula]. When c-ssDNAs are nonrepetitive, then the overall renaturation rate becomes as kR {propto} kNL and one finally obtains [Formula] in line with the experimental observations. When c-ssDNAs are repetitive with a complexity of c, then earlier models suggested the scaling [Formula][Formula] which breaks down at c = L. This clearly suggested the existence of at least two different pathways of renaturation in case of repetitive c-ssDNAs viz. via incorrect contacts and trap correct contacts. The trap correct contacts can lead to the formation of partial duplexes which can keep the complementary strands in the close vicinity for a prolonged timescale. This is essential for the extended 1D slithering, inchworm movements and internal displacement mechanisms which can accelerate the searching for the correct contacts. Clearly, the extent of slithering dynamics will be inversely proportional to the complexity. When the complexity is close to the length of c-ssDNAs, then the pathway via incorrect contacts will dominate. When the complexity is much lesser than the length of c-ssDNA, then pathway via trap correct contacts would be the dominating one.


title: Transcriptomic Profiling Reveals Cancer-Associated Fibroblasts as Potential Targets for the Prognosis and Treatment of Cervical Squamous Cell Carcinoma

abstract: Effective treatment of advanced invasive cervical cancer remains challenging nowadays. Herein, single-nucleus RNA sequencing (snRNA-seq) and SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq) technology are used to investigate the immunological microenvironment of cervical squamous cell carcinoma (CSCC), a major type of cervical cancers. The expression levels of most immune checkpoint genes in tumor and inflammation areas of CSCC were not significantly higher than those in the non-cancer samples except for LGALS9 and IDO1. Stronger signals of CD56+ NK cells and immature dendritic cells are found in the hypermetabolic tumor areas, while more eosinophils, immature B cells, and Treg cells are found in the hypometabolic tumor areas. Moreover, a cluster of cancer-associated fibroblasts (CAFs) are identified around some tumors, which highly expressed ACTA2, POSTN, ITGB4, and FAP. The CAFs might support the growth and metastasis of tumors by inhibiting lymphocyte infiltration and remodeling the tumor extracellular matrix. Furthermore, CAFs are associated with poorer survival probability in CSCC patients and might be present in a small fraction ([~]20%) of advanced cancer patients. Collectively, these findings might enhance understanding of the CSCC immunological microenvironment and shed some light on the treatment of advanced CSCC.

category: cancer biology


title: Single-nucleus RNA Sequencing and Spatial Transcriptomics Reveal the Immunological Microenvironment of Cervical Squamous Cell Carcinoma


title: Activation of retinoic acid receptor reduces metastatic prostate cancer bone lesions through blocking endothelial-to-osteoblast transition

abstract: Metastatic prostate cancer (PCa) in bone induces bone-forming lesions that contribute to progression and therapy resistance. Currently strategies targeting PCa-induced bone formation are lacking. We previously showed that PCa-induced bone originates from endothelial cells (EC) that have undergone endothelial-to-osteoblast (EC-to-OSB) transition in response to tumor-secreted BMP4. Here, we show that activation of retinoic acid receptor (RAR) inhibits EC-to-OSB transition and reduces PCa-induced bone formation. We found that palovarotene, a RAR{gamma} agonist being tested for heterotopic ossification in fibrodysplasia ossificans progressiva, inhibited EC-to-OSB transition and osteoblast mineralization in vitro, and decreased tumor-induced bone formation and tumor growth in several osteogenic PCa models. RAR/{beta}/{gamma} isoform knockdown in 2H11 ECs blocked EC-to-OSB transition and osteoblast mineralization. Pan-RAR agonist ATRA inhibited MycCaP-BMP4-induced bone formation and tumor growth under castration. Furthermore, palovarotene or ATRA reduced plasma Tenascin C, a factor secreted by EC-OSB cells, which may be used to monitor treatment response. Mechanistically, BMP4-activated pSmad1 forms a complex with RAR in the nucleus of 2H11 cells. RAR activation by palovarotene or ATRA causes pSmad1 degradation by recruiting E3-ubiquitin ligase Smurf1 into the nuclear pSmad1/RAR{gamma} complex. Our findings suggest that palovarotene can be repurposed to target PCa-induced bone formation to improve clinical outcomes for bone metastasis.


title: De novo serine biosynthesis from glucose predicts sex-specific response to antifolates in non-small cell lung cancer cell lines

abstract: Lung cancer is the leading cause of cancer-related death. Intriguingly, males with non-small cell lung cancer (NSCLC), the most common type of lung cancer, have a higher mortality rate than females. Here, we investigated the role of serine metabolism as a predictive marker for sensitivity to the antifolate pemetrexed in male and female NSCLC cell lines. Using [13C6] glucose tracing in NSCLC cell lines, we found that male cells generated significantly more serine from glucose than female cells. Higher serine biosynthesis was further correlated with increased sensitivity to pemetrexed in male cells only. Concordant sex differences in metabolic gene expression were evident in NSCLC and pan-cancer transcriptome datasets, suggesting a potential mechanism with wide-reaching applicability. These data were further validated by integrating antifolate drug cytotoxicity and metabolic pathway transcriptome data from pan-cancer cell lines. Together, these findings highlight the importance of considering sex differences in cancer metabolism to improve treatment for all patients.


title: Circulating neurofilament light chain as a promising biomarker of AAV-induced dorsal root ganglia toxicity in nonclinical toxicology species

abstract: Adeno-associated virus (AAV)-induced dorsal root ganglia (DRG) toxicity has been observed in several nonclinical species, where lesions are characterized by neuronal degeneration/necrosis, nerve fiber degeneration, and mononuclear cell infiltration. As AAV vectors become an increasingly common platform for novel therapeutics, non-invasive biomarkers are needed to better characterize and manage the risk of DRG neurotoxicity in both nonclinical and clinical studies. Based on biological relevance, reagent availability, antibody cross-reactivity, DRG protein expression, and assay performance, neurofilament light chain (NF-L) emerged as a promising biomarker candidate. Dose- and time-dependent changes in NF-L were evaluated in male Wistar Han rats and cynomolgus monkeys following intravenous or intrathecal AAV injection, respectively. NF-L profiles were then compared against microscopic DRG lesions on Day 29 post-dosing. In animals exhibiting DRG toxicity, plasma/serum NF-L was strongly associated with the severity of neuronal degeneration/necrosis and nerve fiber degeneration, with elevations beginning as early as Day 8 in rats ([≥]5x1013 vg/kg) and Day 14 in monkeys ([≥]3.3x1013 vg/dose). Consistent with the unique positioning of DRGs outside the blood-brain barrier, NF-L in cerebrospinal fluid was only weakly associated with DRG findings. In summary, circulating NF-L is a promising biomarker of AAV-induced DRG toxicity in nonclinical species.

category: pharmacology and toxicology


title: MALDI mass spectrometry imaging of fresh and processed food: constituents, ingredients, contaminants and additives

abstract:
Mass Spectrometry imaging (MS imaging) provides spatial information for a wide range of compound classes in different sample matrices. We used MS imaging to investigate the distribution of components in fresh and processed food, including meat, dairy and bakery products. The MS imaging workflow was optimized to cater to the specific properties and challenges of the individual samples. We successfully detected highly nonpolar and polar constituents such as beta-carotene and anthocyanins, respectively. For the first time, the distribution of a contaminant and a food additive was visualized in processed food. We detected acrylamide in German gingerbread and investigated the penetration of the preservative natamycin into cheese. For this purpose, a new data analysis tool was developed to study the penetration of analytes from uneven surfaces. Our results show that MS imaging has great potential in food analysis to provide relevant information about components distributions, particularly those underlying official regulations.

HighlightsO_LIInvestigation of fresh and processed food by MALDI mass spectrometry imaging
C_LIO_LIVisualization of different compound classes in plant and meat-based food
C_LIO_LIDevelopment of data processing tool for penetration/diffusion analysis (in food)
C_LIO_LINatamycin penetration in cheese, first visualization of food additive by MS imaging
C_LIO_LIAcrylamide in gingerbread, first visualization of contaminant by MS imaging
C_LI


title: A discovery-based proteomics approach identifies protein disulfide isomerase (PDIA1) as a biomarker of β cell stress in type 1 diabetes

abstract:
BackgroundActivation of stress pathways intrinsic to the {beta} cell are thought to both accelerate {beta} cell death and increase {beta} cell immunogenicity in type 1 diabetes (T1D). However, information on the timing and scope of these responses is lacking.

MethodsTo identify temporal and disease-related changes in islet {beta} cell protein expression, data independent acquisition-mass spectrometry was performed on islets collected longitudinally from NOD mice and NOD-SCID mice rendered diabetic through T cell adoptive transfer.

FindingsIn islets collected from female NOD mice at 10, 12, and 14 weeks of age, we found a time-restricted upregulation of proteins involved in the maintenance of {beta} cell function and stress mitigation, followed by loss of expression of protective proteins that heralded diabetes onset. Pathway analysis identified EIF2 signaling and the unfolded protein response, mTOR signaling, mitochondrial function, and oxidative phosphorylation as commonly modulated pathways in both diabetic NOD mice and NOD-SCID mice rendered acutely diabetic by adoptive transfer, highlighting this core set of pathways in T1D pathogenesis. In immunofluorescence validation studies, {beta} cell expression of protein disulfide isomerase A1 (PDIA1) and 14-3-3b were found to be increased during disease progression in NOD islets, while PDIA1 plasma levels were increased in pre-diabetic NOD mice and in the serum of children with recent-onset T1D compared to age and sex-matched non-diabetic controls.

InterpretationWe identified a common and core set of modulated pathways across distinct mouse models of T1D and identified PDIA1 as a potential human biomarker of {beta} cell stress in T1D.

category: physiology


title: Metal transporter SLC39A14/ZIP14 modulates regulation between the gut microbiome and host metabolism

abstract:
Zinc (Zn) plays a critical role in maintaining intestinal homeostasis by regulating intestinal epithelial cells, host immune cells, and gut microbiome community composition. Deletion of metal transporter Slc39a14/Zip14 causes spontaneous intestinal permeability with low-grade chronic inflammation, mild hyperinsulinemia, and greater body fat with insulin resistance in adipose, suggesting a role for ZIP14-mediated intestinal metal transport in regulating both intestinal homeostasis and systemic metabolism. Here, we showed the function of ZIP14-mediated Zn transport in the gut microbiome composition and how ZIP14-linked changes to gut microbiome community composition are correlated with changes in host metabolism. Deletion of Zip14 generated Zn-deficient epithelial cells and luminal content in the entire intestinal tract; reduced bacterial diversity and Saccharomyces cerevisiae (S. cerevisiae) overgrowth; altered host metabolome; and shifted host energy metabolism toward glucose utilization. This work provides evidence for the regulation of gut microbiome composition, host metabolome, and energy metabolism by metal transporter ZIP14.

SignificanceIntestinal permeability, gut dysbiosis, and Zn dyshomeostasis are emerging signatures of inflammatory bowel diseases and metabolic disorders such as type-2-diabetes and obesity. Zn deficiency is a common clinical finding among these diseases. Zn is essential for the regulation of the intestinal epithelial cells, host immune cells, and the gut microbiome. Transporter-mediated mobilization of Zn plays a critical role in maintaining intestinal homeostasis by facilitating the targeted tissue/cell-specific function. However, studies are lacking in linking transporter-mediated Zn mobilization, gut microbiome, hosts intestinal health, and metabolism. Using the systems-level approach, this study revealed novel findings that deletion of Slc39a14/Zip14 resulted in altered intestinal Zn homeostasis, gut microbiome composition, host metabolome and energy metabolism.


title: Vicia faba TPC1, a genetically encoded variant of the vacuole Two Pore Channel 1, is hyperexcitable

abstract:
To fire action-potential-like electrical signals, the vacuole membrane requires the depolarization-activated two-pore channel TPC1, also called Slowly activating Vacuolar SV channel. The TPC1/SV channel, encoded by the TPC1 gene, functions as a voltage-dependent and Ca2+-regulated potassium channel. TPC1 currents are activated by a rise in cytoplasmic Ca2+ but inhibited by luminal Ca2+. In search for species-dependent functional TPC1 channel variants, we studied polymorphic amino acids contributing to luminal Ca2+ sensitivity. We found that the acidic residues E457, E605 and D606 of the Ca2+-sensitive Arabidopsis AtTPC1 channel were neutralized by either asparagine or alanine in Vicia faba and many other Fabaceae as well. When expressed in the Arabidopsis loss-of-AtTPC1 function background, the wild type VfTPC1 was hypersensitive to vacuole depolarization and insensitive to blocking luminal Ca2+. When AtTPC1 was mutated for the three VfTPC1-homologous polymorphic site residues, the Arabidopsis At-VfTPC1 channel mutant gained VfTPC1-like voltage and luminal Ca2+ insensitivity that together made vacuoles hyperexcitable. These findings indicate that natural TPC1 channel variants in plant families exist which differ in vacuole excitability and very likely respond to changes in environmental settings of their ecological niche.

Significance statementVacuolar electrical excitability and stress-related Ca2+ signaling depends on the activity of the vacuolar cation channel TPC1. Until now, the regulatory features of AtTPC1 from the model plant Arabidopsis thaliana was believed to apply to the TPC1 channels of other species. However, here we now show that, surprisingly, the VfTPC1 channel of the economic broad bean, in contrast to AtTPC1, proves to be hyperactive and confers hyperexcitability to the vacuole. The different gating behavior is most likely related to an impaired Ca2+ sensor site in the vacuolar pore vestibule, rising the probability to open at more negative membrane voltages. These natural variants of the TPC1 channel could help the plant adapt and respond to environmental challenges.

category: plant biology


title: Experimental platform for the functional investigation of membrane proteins in giant unilamellar vesicles

abstract: Giant unilamellar vesicles (GUVs) are micrometer-sized model membrane systems that can be viewed directly under the microscope. They serve as scaffolds for the bottom-up creation of synthetic cells, targeted drug delivery and have been used in many in vitro studies of membrane related phenomena. GUVs are also of interest for the functional investigation of membrane proteins that carry out many key cellular functions. A major hurdle to a wider application of GUVs in this field is the diversity of existing protocols that are optimized for individual proteins. Here, we compare PVA assisted and electroformation techniques for GUV formation under physiologically relevant conditions, and analyze the effect of immobilization on vesicle structure and membrane tightness towards small substrates and protons. There, differences in terms of yield, size, and leakage of GUVs produced by PVA assisted swelling and electroformation were found, dependent on salt and buffer composition. Using fusion of oppositely charged membranes to reconstitute a model membrane protein, we find that empty vesicles and proteoliposomes show similar fusion behavior, which allows for a rapid estimation of protein incorporation using fluorescent lipids.

category: synthetic biology


title: Network design principle for robust oscillatory behaviors with respect to biological noise

abstract: Oscillatory behaviors, which are ubiquitous in transcriptional regulatory networks, are often subject to inevitable biological noise. Thus a natural question is how transcriptional regulatory networks can robustly achieve accurate oscillation in the presence of biological noise. Here, we search all two- and three-node transcriptional regulatory network topologies for those robustly capable of accurate oscillation against the parameter variability (extrinsic noise) or stochasticity of chemical reactions (intrinsic noise). We find that, no matter what source of the noise is applied, the topologies containing the repressilator with positive auto-regulation show higher robustness of accurate oscillation than those containing the activator-inhibitor oscillator, and additional positive auto-regulation enhances the robustness against noise. Nevertheless, the attenuation of different sources of noise is governed by distinct mechanisms: the parameter variability is buffered by the long period, while the stochasticity of chemical reactions is filtered by the high amplitude. Furthermore, we analyze the noise of a synthetic human nuclear factor {kappa}B (NF-{kappa}B) signaling network by varying three different topologies, and verify that the addition of a repressilator to the activator-inhibitor oscillator, which leads to the emergence of high-robustness motif--the repressilator with positive auto-regulation, improves the oscillation accuracy in comparison to the topology with only an activator-inhibitor oscillator. These design principles may be applicable to other oscillatory circuits.

category: systems biology


title: Biological regulatory networks are less nonlinear than expected by chance

abstract: AO_SCPLOWBSTRACTC_SCPLOWNonlinearity is a characteristic of complex biological regulatory networks that has implications ranging from therapy to control. To better understand its nature, we analyzed a suite of published Boolean network models, containing a variety of complex nonlinear interactions, with an approach involving a probabilistic generalization of Boolean logic that George Boole himself had proposed. Leveraging the continuous-nature of this formulation using Taylor-decomposition methods revealed the distinct layers of nonlinearity of the models. A comparison of the resulting series of model-approximations with the corresponding sets of randomized ensembles furthermore revealed that the biological networks are relatively more linearly approximable. We hypothesize that this is a result of optimization by natural selection for the purpose of controllability.


title: A systems approach discovers the role and characteristics of seven LysR type transcription factors in Escherichia coli

abstract:
Although Escherichia coli K-12 strains represent perhaps the best known model bacteria, we do not know the identity or functions of all of their transcription factors (TFs). It is now possible to systematically discover the physiological function of TFs in E. coli BW25113 using a set of synergistic methods; including ChIP-exo, growth phenotyping, conserved gene clustering, and transcriptome analysis. Among 47 LysR-type TFs (LTFs) found on the E. coli K-12 genome, many regulate nitrogen source utilization or amino acid metabolism. However, 19 LTFs remain unknown. In this study, we elucidated the regulation of seven of these 19 LTFs: YbdO, YbeF, YgfI, YiaU, YneJ, YcaN, YbhD. We show that: 1) YbdO regulation has an effect on bacterial growth at low pH with citrate supplementation. YbdO is a repressor of the ybdNM operon and is implicated in the regulation of citrate lyase genes (citCDEFG); 2) YgfI activates the dhaKLM operon that encodes the phosphotransferase system involved in glycerol and dihydroxyacetone utilization; 3) YiaU regulates the yiaT gene encoding an outer membrane protein, and waaPSBOJYZU operon is also important in determining cell density at the stationary phase; 4) YneJ, re-named here as PtrR, directly regulates the expression of the succinate-semialdehyde dehydrogenase, Sad (also known as YneI), and is a predicted regulator of fnrS (a small RNA molecule). PtrR is important for bacterial growth in the presence of L-glutamate and putrescine as nitrogen sources; and 5) YbhD and YcaN regulate adjacent y-genes on the genome and YbeF is involved in flagella gene regulation. We have thus established the functions for four LTFs and identified the target genes for three LTFs.

IMPORTANCEThe reconstruction of the transcriptional regulatory network (TRN) is important for gram-negative bacteria such as E. coli. LysR-type TFs are abundant in Enterobacteria, but many LTF functions still remain unknown. Here we report putative functions of uncharacterized TFs based on multi-omics data related to L-threonine, L-glutamate, and putrescine utilization. Amino acids (AAs) and polyamines are important sources of nitrogen for many microorganisms, but the increase in one amino acid or putrescine concentration in a minimal medium also induces stress. Although polyamine metabolism has been studied, the TRN that controls the putrescine (Ptr) and AA utilization at minimal medium conditions are still poorly understood. The function of previously uncharacterized transcriptional regulators YbdO, YgfI, and YneJ (PtrR) were identified in Escherichia coli. PtrR is important for Ptr and L-glutamate utilization, while YgfI transcriptional regulation was found to be important for growth on L-threonine and glycerol as a carbon source.


title: Positive supercoiling buildup is a trigger of E. coli's short-term response to cold shock

abstract: Adaptation to cold shock (CS) is a key survival skill of gut bacteria of warm-blooded animals. In E. coli, this skill emerges from a complex transcriptional program of multiple, timely-ordered shifts in gene expression. We identified short-term, cold shock repressed (CSR) genes by RNA-seq and provide evidence that their variability in evolutionary fitness is low and that their responsiveness to cold emanates from intrinsic features. Given that their single-cell variability in protein numbers increases after CS, we hypothesized that the responsiveness of a large portion of CSR genes is triggered by the high propensity for transcription locking due to positive supercoiling buildup (PSB). We then proposed a model of this phenomenon and, in support, show that nearly half of CSR genes are highly responsive to Gyrase inhibition. Also, their response strengths to CS and Gyrase inhibition correlate and most CSR genes increase their single-cell variability in protein numbers. Further, during CS, the cells nucleoid density increases (in agreement with increased numbers of positive supercoils), their energy levels become depleted (while the resolving of positive supercoils is ATP dependent), and the colocalization of Gyrases and the nucleoid increases (in agreement with increased time length for resolving supercoils). We conclude that high sensitivity to PSB is at the core of the short-term, cold shock responsive transcriptional program of E. coli and propose that this gene feature may be useful for providing temperature sensitivity to chromosome-integrated synthetic circuits.


title: Image-based taxonomic classification of bulk biodiversity samples using deep learning and domain adaptation

abstract: Complex bulk samples of invertebrates from biodiversity surveys present a great challenge for taxonomic identification, especially if obtained from unexplored ecosystems. High-throughput imaging combined with machine learning for rapid classification could overcome this bottleneck. Developing such procedures requires that taxonomic labels from an existing source data set are used for model training and prediction of an unknown target sample. Yet the feasibility of transfer learning for the classification of unknown samples remains to be tested. Here, we assess the efficiency of deep learning and domain transfer algorithms for family-level classification of below-ground bulk samples of Coleoptera from understudied forests of Cyprus. We trained neural network models with images from local surveys versus global databases of above-ground samples from tropical forests and evaluated how prediction accuracy was affected by: (a) the quality and resolution of images, (b) the size and complexity of the training set and (c) the transferability of identifications across very disparate source-target pairs that do not share any species or genera. Within-dataset classification accuracy reached 98% and depended on the number and quality of training images and on dataset complexity. The accuracy of between-datasets predictions was reduced to a maximum of 82% and depended greatly on the standardisation of the imaging procedure. When the source and target images were of similar quality and resolution, albeit from different faunas, the reduction of accuracy was minimal. Application of algorithms for domain adaptation significantly improved the prediction performance of models trained by non-standardised, low-quality images. Our findings demonstrate that existing databases can be used to train models and successfully classify images from unexplored biota, when the imaging conditions and classification algorithms are carefully considered. Also, our results provide guidelines for data acquisition and algorithmic development for high-throughput image-based biodiversity surveys.

category: zoology


title: Opioid withdrawal abruptly disrupts amygdala circuit function by reducing peptide actions

abstract:
Opioid withdrawal drives relapse and contributes to compulsive drug use through disruption of endogenous opioid dependent learning circuits in the amygdala. Normally, endogenous opioids control these circuits by inhibiting glutamate release from basolateral amygdala principal neurons onto GABAergic intercalated cells. Using patch-clamp electrophysiology in rat brain slices, we reveal that opioid withdrawal dials down this endogenous opioid inhibition of synaptic transmission. Peptide activity is dialled down due to a protein kinase A dependent increase in the activity of the peptidase, neprilysin. This disrupts peptidergic control of both GABAergic and glutamatergic transmission through multiple amygdala circuits, including reward-related outputs to the nucleus accumbens. This likely disrupts peptide-dependent learning processes in the amygdala during withdrawal. and may direct behaviour towards compulsive drug use. Restoration of endogenous peptide activity during withdrawal may be a viable option to normalise synaptic transmission in the amygdala and restore normal reward learning.

In BriefWe find that opioid withdrawal dials down inhibitory neuropeptide activity in the amygdala. This disrupts both GABAergic and glutamatergic transmission through amygdala circuits, including reward-related outputs to the nucleus accumbens. This likely disrupts peptide-dependent learning processes in the amygdala during withdrawal and may direct behaviour towards compulsive drug use.

HighlightsO_LIDuring opioid withdrawal, peptidase activity is upregulated in an amygdala circuit
C_LIO_LIPeptidase upregulation occurs via a PKA-dependent mechanism
C_LIO_LIIncreased peptidase activity limits peptidergic control of synaptic transmission
C_LIO_LIOpioid withdrawal disrupts the balance of excitation and inhibition in the amygdala
C_LI

category: neuroscience


title: Chronic Alcohol Dysregulates Glutamatergic Function in the Basolateral Amygdala in a Projection- and Sex-Specific Manner

abstract: Chronic intermittent ethanol (CIE) produces alcohol dependence, facilitates anxiety-like behavior, and increases post-CIE alcohol intake. The basolateral amygdala (BLA) is one of several brain regions that regulates anxiety-like behavior and alcohol intake through downstream projections. The BLA receives information from two distinct input pathways. Afferents from medial structures like the thalamus and prefrontal cortex enter the BLA through the stria terminalis whereas lateral cortical structures like the anterior insula cortex enter the BLA through the external capsule. CIE induces input- and sex-specific adaptations to glutamatergic function in the BLA. Previous studies sampled neurons throughout the BLA, but did not distinguish between projection-specific populations. The current study investigated BLA neurons that project to the NAC (BLA-NAC neurons) or the BNST (BLA-BNST neurons) as representative  reward and  aversion BLA neurons, and showed that CIE alters glutamatergic function and excitability in a projection- and sex-specific manner. CIE increases glutamate release from stria terminalis inputs only onto BLA-BNST neurons. At external capsule synapses, CIE increases postsynaptic glutamatergic function in male BLA-NAC neurons and female BLA-BNST neurons. Subsequent experiments demonstrated that CIE enhanced the excitability of male BLA-NAC neurons and BLA-BNST neurons in both sexes when glutamatergic but not GABAergic function was intact. Thus, CIE-mediated increased glutamatergic function facilitates hyperexcitability in male BLA-NAC neurons and BLA-BNST neurons of both sexes.


title: Cannabinoid during adolescence phenocopies reelin haploinsufficiency in prefrontal cortex synapses

abstract: In humans and rodents, the protracted development of the prefrontal cortex (PFC) throughout adolescence represents a time for marked vulnerability towards environmental adversities, such as stress or drug exposure. We previously showed that the extracellular matrix protein reelin is an instrumental synaptic modulator that shapes medial PFCs (mPFC) circuitry during maturation and is a critical mediator of the vulnerability to environmental stress. Emerging evidence highlight the role of the endocannabinoid system in the postnatal maturation of the PFC and reelin deficiency influences behavioral abnormalities caused by heavy consumption of THC during adolescence. Could the reelin-dependent maturation of prefrontal networks may be vulnerable to cannabinoid exposure during adolescence? To explore this hypothesis, we studied the effects of a single in-vivo exposure to a synthetic cannabinoid on reelin expression and mPFC functions in adolescent male mice. The results show that a single cannabinoid exposure mimics reelin haploinsufficiency by decreasing prefrontal reelin expression in a layer-specific pattern without changing its transcriptional levels. Furthermore, this treatment impeded synaptic plasticity: adolescent cannabinoid lowered long-term potentiation to the magnitude observed in age-matched reelin haploinsufficient males. Quantitative PCR analysis showed that changes in the mRNA levels of NMDARs does not account for the reduction of TBS-LTP. Together, the data show that exposure to cannabinoid during adolescence phenocopies reelin haploinsufficiency and further identifies reelin as a key component of the vulnerability of PFC to environmental insults.


title: Multimodal fusion analysis of functional, cerebrovascular and structural neuroimaging in healthy ageing subjects

abstract: Cognitive ageing is a complex process which requires multimodal approach. Neuroimaging can provide insights into brain morphology, functional organization and vascular dynamics. However, most neuroimaging studies of ageing have focused on each imaging modality separately, limiting the understanding of interrelations between processes identified by different modalities and the interpretation of neural correlates of cognitive decline in ageing. Here, we used linked independent component analysis as a data-driven multimodal approach to jointly analyze magnetic resonance imaging of grey matter density, cerebrovascular, and functional network topographies. Neuroimaging and behavioural data (n = 215) from the Cambridge Centre for Ageing and Neuroscience study were used, containing healthy subjects aged 18 to 88. In the output components, fusion was found between structural and cerebrovascular topographies in multiple components with cognitive-relevance across the lifespan. A component reflecting global atrophy with regional cerebrovascular changes and a component reflecting right frontoparietal network activity were correlated with fluid intelligence over and above age and gender. No meaningful fusion between functional network topography and structural or cerebrovascular signals was observed. We propose that integrating multiple neuroimaging modalities allows to better characterize brain pattern variability and to differentiate brain changes in healthy ageing.


title: Dissociable roles for the striatal cholinergic system in different flexibility contexts.

abstract: The production of behavioural flexibility requires the coordination and integration of information from across the brain, by the dorsal striatum. In particular, the striatal cholinergic system is thought to be important for the modulation of striatal activity. Research from animal literature has shown that chemical inactivation of the dorsal striatum leads to impairments in reversal learning. Furthermore, proton magnetic resonance spectroscopy work has shown that the striatal cholinergic system is also important for reversal learning in humans. Here, we aim to assess whether the state of the dorsal striatal cholinergic system at rest is related to flexible behaviour in reversal learning. We provide preliminary results showing that variability in choline in the dorsal striatum is significantly related to both the number perseverative and regressive errors that participants make, and their rate of learning from positive and negative prediction errors. These findings, in line with previous work, suggest the resting state of dorsal striatal cholinergic system has important implications for producing flexible behaviour. However, these results also suggest the system may have heterogeneous functionality across different types of tasks measuring behavioural flexibility. These findings provide a starting point for further interrogation into understanding the functional role of the striatal cholinergic system in flexibility.


title: The what and where of synchronous sound perception

abstract:
AO_SCPLOWBSTRACTC_SCPLOWSound localization and identification are challenging in acoustically rich environments. The relation between these two processes is still poorly understood. As natural sound-sources rarely occur exactly simultaneously, we wondered whether the auditory system could identify ("what") and localize ("where") two spatially separated sounds with synchronous onsets. While listeners typically report hearing a single source at an average location, one study found that both sounds may be accurately localized if listeners are explicitly being told two sources exist. We here tested whether simultaneous source identification (one vs. two) and localization is possible, by letting listeners choose to make either one or two head-orienting saccades to the perceived location(s). Results show that listeners could identify two sounds only when presented on different sides of the head, and that identification accuracy increased with their spatial separation. Notably, listeners were unable to accurately localize either sound, irrespective of whether one or two sounds were identified. Instead, the first (or only) response always landed near the average location, while second responses were unrelated to the targets. We conclude that localization of synchronous sounds in the absence of prior information is impossible. We discuss that the putative cortical  what pathway may not transmit relevant information to the  where pathway. We examine how a broadband interaural correlation cue could help to correctly identify the presence of two sounds without being able to localize them. We propose that the persistent averaging behavior reveals that the  where system intrinsically assumes that synchronous sounds originate from a single source.

SO_SCPLOWIGNIFICANCEC_SCPLOW SO_SCPLOWTATEMENTC_SCPLOWIt is poorly understood whether identification ( what) of sounds and their localization ( where) are inter-related, or independent neural processes. We measured sound-localization responses towards synchronous sounds to examine potential coupling of these processes. We varied the spatial configurations of two sounds and found that although identification improved considerably with larger spatial separation, their localization was unaffected: responses were always directed towards the average location. This shows absence of mutual coupling of information between the  what and  where streams in the auditory system. We also show how broadband interaural correlation could explain the improved identification results, without affecting localization performance, and explain how the persistent spatial averaging could be understood from strong internal priors regarding sound synchronicity.


title: Taking stock of the past: A psychometric evaluation of the Autobiographical Interview

abstract: Autobiographical memory (AM) involves a rich phenomenological re-experiencing of a spatio-temporal event from the past, which is challenging to objectively quantify. The Autobiographical Interview (AI; Levine et al., 2002, Psychology & Aging) is a manualized performance-based assessment designed to quantify episodic (internal) and semantic (external) features of recalled and verbally conveyed prior experiences. The AI has been widely adopted yet has not undergone a comprehensive psychometric validation. We investigated the reliability, validity, association to individual differences measures, and factor structure in healthy younger and older adults (N=352). Evidence for the AIs reliability was strong: the subjective scoring protocol showed high inter-rater reliability and previously identified age effects were replicated. Internal consistency across timepoints was robust, suggesting stability in recollection. Central to our validation, internal AI scores were positively correlated with standard, performance-based measures of episodic memory, demonstrating convergent validity. The two-factor structure for the AI was not well-supported by confirmatory factor analysis. Adjusting internal and external detail scores for the number of words spoken (detail density) improved trait estimation of AM performance. Overall, the AI demonstrated sound psychometric properties for inquiry into the qualities of autobiographical remembering.


title: Neural correlates of perceiving and interpreting engraved prehistoric patterns as human production: effect of archaeological expertise.

abstract: It has been suggested that engraved abstract patterns dating from the Middle and Lower Palaeolithic served as means of representation and communication. Identifying the brain regions involved in visual processing of these engravings can provide insights into their function. In this study, brain activity was measured during perception of the earliest known Palaeolithic engraved patterns and compared to natural patterns mimicking human-made engravings. Participants were asked to categorise marks as being intentionally made by humans or due to natural processes (e.g. erosion, root etching). To simulate the putative familiarity of our ancestors with the marks, the responses of expert archaeologists and control participants were compared, allowing characterisation of the effect of previous knowledge on both behaviour and brain activity in perception of the marks. Besides a set of regions common to both groups and involved in visual analysis and decision-making, the experts exhibited greater activity in the inferior part of the lateral occipital cortex, ventral occipitotemporal cortex, and medial thalamic regions. These results are consistent with those reported in visual expertise studies, and confirm the importance of the integrative visual areas in the perception of the earliest abstract engravings. The attribution of a natural rather than human origin to the marks elicited greater activity in the salience network in both groups, reflecting the uncertainty and ambiguity in the perception of, and decision-making for, natural patterns. The activation of the salience network might also be related to the process at work in the attribution of an intention to the marks. The primary visual area was not specifically involved in the visual processing of engravings, which argued against its central role in the emergence of engraving production.


title: SEX-SPECIFIC TRAJECTORIES OF REELIN-DEPENDENT MATURATION OF DEEP LAYER PREFRONTAL NEURONS

abstract: Throughout early adulthood, the anatomical and functional maturation of PFC circuitry continues under the influence of multiple extrinsic and intrinsic factors, most notably electrical activity, and molecular cues. We previously showed that the extracellular matrix protein reelin orchestrates the structural and functional maturation of deep layers medial PFC (mPFC) pyramidal neurons. Additionally, we reported that reelin haploinsufficiency is associated to prefrontal disruptions of long-term memory retention thereby illustrating the eminent role of reelin in cognitive maturation of the PFC. Prefrontal maturation follows a sex-specific developmental pattern, supporting the existence of sexual differences in the morphology-functional properties PFC. Here, we interrogated the role of reelin in the functional maturation of excitatory networks in the mPFC. The developmental trajectory of reelins expression and deep layer pyramidal neurons synaptic plasticity was tracked in the mPFC of male and female mice, from the juvenile period to adulthood. To assess the role of reelin in both sexes, wild-type and heterozygous reeler mice (HRM) were compared. The results show that the maturational profile of reelin expression in the mPFC is sex-dependent and that the developmental trajectory of long-term potentiation is different between wild-type males and females. These data demonstrate reelins influence on prefrontal synapses is sex and period specific.


title: Extracting dynamical understanding from neural-mass models of mouse cortex

abstract: New brain atlases with high spatial resolution and whole-brain coverage have rapidly advanced our knowledge of the brains neural architecture, including the systematic variation of excitatory and inhibitory cell densities across the mammalian cortex. But understanding how the brains microscale physiology shapes brain dynamics at the macroscale has remained a challenge. While physiologically based mathematical models of brain dynamics are well placed to bridge this explanatory gap, their complexity can form a barrier to providing clear mechanistic interpretation of the dynamics they generate. In this work we develop a neural-mass model of the mouse cortex and show how bifurcation diagrams, which capture local dynamical responses to inputs and their variation across brain regions, can be used to understand the resulting whole-brain dynamics. We show that strong fits to resting-state functional magnetic resonance imaging (fMRI) data can be found in surprisingly simple dynamical regimes--including where all brain regions are confined to a stable fixed point--in which regions are able to respond strongly to variations in their inputs, consistent with direct structural connections providing a strong constraint on functional connectivity in the anesthetized mouse. We also use bifurcation diagrams to show how perturbations to local excitatory and inhibitory coupling strengths across the cortex, constrained by cell-density data, provide spatially dependent constraints on resulting cortical activity, and support a greater diversity of coincident dynamical regimes. Our work illustrates methods for visualizing and interpreting model performance in terms of underlying dynamical mechanisms, an approach that is crucial for building explanatory and physiologically grounded models of the dynamical principles that underpin large-scale brain activity.


title: Neural mechanisms of credit assignment for inferred relationships in a structured world

abstract: Animals have been proposed to abstract compact representations of a tasks structure that could, in principle, support accelerated learning and flexible behavior. Whether and how such abstracted representations may be used to assign credit for inferred, but unobserved, relationships in structured environments are unknown. Here, we develop a novel hierarchical reversal-learning task and Bayesian learning model to assess the computational and neural mechanisms underlying how humans infer specific choice-outcome associations via structured knowledge. We find that the medial prefrontal cortex (mPFC) efficiently represents hierarchically related choice-outcome associations governed by the same latent cause, using a generalized code to assign credit for both experienced and inferred outcomes. Furthermore, mPFC and lateral orbital frontal cortex track the inferred current "position" within a latent association space that generalizes over stimuli. Collectively, these findings demonstrate the importance both of tracking the current position in an abstracted task space and efficient, generalizable representations in prefrontal cortex for supporting flexible learning and inference in structured environments.


title: Flexible and efficient simulation-based inference for models of decision-making

abstract: Identifying parameters of computational models that capture experimental data is a central task in cognitive neuroscience. Bayesian statistical inference aims to not only identify a single configuration of best-fitting parameters, but to recover all model parameters that are consistent with the data and prior knowledge. Statistical inference methods usually require the ability to evaluate the likelihood of the model--however, for many models of interest in cognitive neuroscience, the associated likelihoods cannot be computed efficiently. Simulation-based inference (SBI) offers a solution to this problem by only requiring access to simulations produced by the model. Here, we provide an efficient SBI method for models of decision-making. Our approach, Mixed Neural Likelihood Estimation (MNLE), trains neural density estimators on model simulations to emulate the simulator. The likelihoods of the emulator can then be used to perform Bayesian parameter inference on experimental data using standard approximate inference methods like Markov Chain Monte Carlo sampling. While most neural likelihood estimation methods target continuous data, MNLE works with mixed data types, as typically obtained in decision-making experiments (e.g., binary decisions and associated continuous reaction times). We demonstrate MNLE on two variants of the drift-diffusion model (DDM) and compare its performance to a recently proposed method for SBI on DDMs, called likelihood approximation networks (LAN, Fengler et al. 2021). We show that MNLE is substantially more efficient than LANs, requiring six orders of magnitudes fewer model simulations to achieve comparable likelihood accuracy and evaluation time while providing the same level of flexibility. We include an implementation of our algorithm in the user-friendly open-source package sbi.


title: An ensemble of toxic channel types underlies the severity of the de novo variant G375R of the human BK channel

abstract:
De novo mutations play a prominent role in neurodevelopmental diseases including autism, schizophrenia, and intellectual disability. Many de novo mutations are dominant and so severe that the afflicted individuals do not reproduce, so the mutations are not passed into the general population. For multimeric proteins, such severity may result from a dominant-negative effect where mutant subunits assemble with WT to produce channels with adverse properties. Here we study the de novo variant G375R heterozygous with the WT allele for the large conductance voltage- and Ca2+-activated potassium (BK channel, Slo1. This variant has been reported to produce devastating neurodevelopmental disorders in three unrelated children. If mutant and WT subunits assemble randomly to form tetrameric BK channels, then ~6% of the assembled channels would be wild type (WT, ~88% would be heteromeric incorporating from 1-3 mutant subunits per channel, and ~6% would be homomeric mutant channels consisting of four mutant subunits. To test this hypothesis, we analyzed the biophysical properties of the single BK channels in the ensemble of channels expressed following a 1:1 injection of mutant and WT cRNA into oocytes. We found ~3% were WT channels, ~85% were heteromeric channels, and ~12% were homomeric mutant channels. All of the heteromeric channels as well as the homomeric mutant channels displayed toxic properties, indicating a dominant negative effect of the mutant subunits. The toxic channels were open at inappropriate negative voltages, even in the absence of Ca2+, which would lead to altered cellular function and decreased neuronal excitability.

SignificanceWe examined the molecular basis for a severe channelopathy associated with developmental and neurological disorders for a de novo variant of the Ca2+-activated potassium (BK) channel, Slo1. To identify the types of BK channels underlying the pathogenicity of the variant, we recorded from BK channels expressed for the G375R mutation heterozygous with the WT allele. We found five different functional types of BK channels, four of which displayed a gain of function toxicity by shifting channel opening to more negative voltages in proportion to the number of mutant subunits per channel and WT. The aberrant channels would disrupt cellular function and the normal electrical activity of neurons, providing a molecular basis for the severity of the phenotype.


title: Distribution of phosphorylated alpha-synuclein in non-diseased brain implicates olfactory bulb mitral cells in synucleinopathy pathogenesis

abstract: Synucleinopathies including Parkinsons disease and dementia with Lewy bodies are neurodegenerative diseases characterized by the intracellular accumulation of the protein alpha-synuclein called "Lewy pathology." Alpha-synuclein within Lewy pathology is aggregated into protease resistant filamentous structures and is predominantly phosphorylated at serine 129 (PSER129). Lewy pathology has been hypothesized to spread throughout the nervous system as the disease progresses. Cross-sectional studies have shown the olfactory bulb and olfactory tract consistently bare LP for common synucleinopathies, making these structures likely starting points for the spreading process, and thus disease. Here we examined the distribution of PSER129 in non-diseased brain. To do this we used a sensitive tyramide signal amplification (TSA) technique to detect low abundance endogenous PSER129 under ideal antibody binding conditions. In wild-type non-diseased mice, PSER129 was detected in the olfactory bulb and several brain regions of the olfactory cortex across the neuroaxis (i.e., olfactory bulb to brain stem). PSER129 was particularly apparent in the mitral cell layer and the outer plexiform layer of the olfactory bulb where it was observed as cytosolic/nuclear puncta or fibers, respectively. PSER129 immunoreactivity in the healthy olfactory bulb was abolished by pretreatment of the tissue with proteinase K, pre-absorption of the primary antibody against the purified PSER129 peptide fragment, or the omission of the PSER129 antibody. Furthermore, PSER129 immunoreactivity was not observed in any brain region of alpha-synuclein knockout mice. Dual labeling for the PSER129 and the mitral cell marker TBX21 showed that PSER129 positive structures of the healthy OB were found in mitral cells. We found evidence of the same PSER129 positive structures in the olfactory bulb of non-diseased rats, non-human primates, healthy humans, but not individuals diagnosed with PD. Results suggest biological pathways responsible for alpha-synuclein phosphorylation are constitutively active in OB mitral cells and alpha-synuclein in these cells may be predisposed to pathological aggregation. Pathological seeds originating in mitral cells may act as a source for alpha-synuclein spread competent assemblies that spreads throughout the brain via fibers of the olfactory tract. Future studies should investigate the normal function of alpha-synuclein in the mitral cells of the olfactory bulb, which may give insight into synucleinopathy disease origins.


title: Type I Interferon Signaling Drives Microglial Dysfunction and Senescence in Human iPSC Models of Down Syndrome and Alzheimers Disease

abstract: Microglia are critical for brain development and play a central role in Alzheimers disease (AD) etiology. Down syndrome (DS), also known as trisomy 21, is the most common genetic origin of intellectual disability and the most common risk factor for AD. Surprisingly, little information is available on the impact of trisomy of human chromosome 21 (Hsa21) on microglia in DS brain development and AD in DS (DSAD). Using our new induced pluripotent stem cell (iPSC)-based human microglia-containing cerebral organoid and chimeric mouse brain models, here we report that DS microglia exhibit enhanced synaptic pruning function during brain development. Consequently, electrophysiological recordings demonstrate that DS microglial mouse chimeras show impaired synaptic neurotransmission, as compared to control microglial chimeras. Upon being exposed to human brain tissue-derived soluble pathological tau, DS microglia display dystrophic phenotypes in chimeric mouse brains, recapitulating microglial responses seen in human AD and DSAD brain tissues. Further flow cytometry, single-cell RNA-sequencing, and immunohistological analyses of chimeric mouse brains demonstrate that DS microglia undergo cellular senescence and exhibit elevated type I interferon signaling after being challenged by pathological tau. Mechanistically, we find that shRNA-mediated knockdown of Hsa21encoded type I interferon receptor genes, IFNARs, rescues the defective DS microglial phenotypes both during brain development and in response to pathological tau. Our findings provide first in vivo evidence supporting a paradigm shifting theory that human microglia respond to pathological tau by exhibiting accelerated senescence and dystrophic phenotypes. Our results further suggest that targeting IFNARs may improve microglial functions during DS brain development and prevent human microglial senescence in DS individuals with AD.


title: Fibroblast growth factor-9 expression in airway epithelial cells amplifies the type I interferon response and alters influenza A virus pathogenesis

abstract:
Influenza A virus (IAV) preferentially infects conducting airway and alveolar epithelial cells in the lung. The outcome of these infections is impacted by the host response, including the production of various cytokines, chemokines, and growth factors. Fibroblast growth factor-9 (FGF9) is required for lung development, can display antiviral activity in vitro, and is upregulated in asymptomatic patients during early IAV infection. We therefore hypothesized that FGF9 would protect the lungs from respiratory virus infection and evaluated IAV pathogenesis in mice that overexpress FGF9 in club cells in the conducting airway epithelium (FGF9-OE mice). However, we found that FGF9-OE mice were highly susceptible to IAV and Sendai virus infection compared to control mice. FGF9-OE mice displayed elevated and persistent viral loads, increased expression of cytokines and chemokines, and increased numbers of infiltrating immune cells as early as 1 day post-infection (dpi). Gene expression analysis showed an elevated type I interferon (IFN) signature in the conducting airway epithelium and analysis of IAV tropism uncovered a dramatic shift in infection from the conducting airway epithelium to the alveolar epithelium in FGF9-OE lungs. These results demonstrate that FGF9 signaling primes the conducting airway epithelium to rapidly induce a localized, protective IFN and proinflammatory cytokine response during viral infection. Although this response protects the airway epithelial cells from IAV infection, it allows for early and enhanced infection of the alveolar epithelium, ultimately leading to increased morbidity and mortality. Our study illuminates a novel role for FGF9 in regulating respiratory virus infection and pathogenesis.

Author SummaryInfluenza viruses are respiratory viruses that cause significant morbidity and mortality worldwide. In the lungs, influenza A virus primarily infects epithelial cells that line the conducting airways and alveoli. Fibroblast growth factor-9 (FGF9) is a growth factor that has been shown to have antiviral activity and is upregulated during early IAV infection in asymptomatic patients, leading us to hypothesize that FGF9 would protect the lung epithelium from IAV infection. However, mice that express and secrete FGF9 from club cells in the conducting airway had more severe respiratory virus infection and a hyperactive inflammatory immune response as early as 1 day post-infection. Analysis of the FGF9-expressing airway epithelial cells found an elevated antiviral and inflammatory interferon signature, which protected these cells from severe IAV infection. However, heightened infection of alveolar cells resulted in excessive inflammation in the alveoli, resulting in more severe disease and death. Our study identifies a novel antiviral and inflammatory role for FGFs in the lung airway epithelium and confirms that early and robust IAV infection of alveolar cells results in more severe disease.

category: immunology


title: Transcriptome features of trained immunity in Drosophila

abstract:
Immune memory is an ability of organisms to potentiate immune responses at secondary infection. Current studies have revealed that innate immunity, as well as adaptive immunity, exhibits the memory character called "trained immunity". Although it is suggested that epigenetic reprogramming plays important roles in trained immunity, its underlying mechanism is not fully understood, especially on the individual level.

Here we established experimental systems for detecting trained immunity in Drosophila melanogaster. Namely, training infection with low-pathogenic bacteria enhanced the survival rate of the flies at subsequent challenge infection with high-pathogenic bacteria. We found that among low-pathogenic bacteria, Micrococcus luteus (Ml) and Salmonella typhimurium (St) mediated apparent training effects in fly, but seemed to act through different ways. Ml left training effects even after its removal from flies, while living St persisted inside flies for a long time. Our RNA-Seq analysis revealed that Ml-training enhanced the expression of immune-related genes during the challenge infection, but did not do so without challenge infection. In contrast, St-training maintained high expression of the immune-related genes with or without challenge. These results suggest that training effects with Ml and St were due to memory and persistence of immune responses, respectively. Furthermore, we searched the factor involved in Ml-training and identified a candidate, Ada2b, which is a component of the histone modification complex. We found that the Ada2b RNAi and mutant flies showed dampened enhancement of survival rates after Ml-training. These results suggest that Ada2b is involved in the Drosophila trained immunity.


title: Molecular insights into antibody-mediated protection against the prototypic simian immunodeficiency virus

abstract: SIVmac239 infection of macaques is a favored model of human HIV infection. However, the SIVmac239 envelope (Env) trimer structure, glycan occupancy, and the targets and ability of neutralizing antibodies (nAbs) to protect against SIVmac239 remain unknown. Here, we report the isolation of SIVmac239 nAbs that recognize a glycan hole and the V1/V4 loop. A high-resolution structure of a SIVmac239 Env trimer-nAb complex shows many similarities to HIV and SIVcpz Envs, but with distinct V4 features and an extended V1 loop. Moreover, SIVmac239 Env has a higher glycan shield density than HIV Env that may contribute to poor or delayed nAb responses in SIVmac239-infected macaques. Passive transfer of a nAb protects macaques from repeated low dose intraveneous SIVmac239 challenge at serum titers comparable to those described for protection of humans against HIV infection. Our results provide structural insights for vaccine design and shed light on antibody-mediated protection in the SIV model.


title: Estimating Microbial Population Data from Optical Density

abstract: The spectrophotometer has been used for decades to measure the density of bacterial populations using the turbidity expressed as optical density - OD. However, the OD alone is an unreliable metric and is only proportionately accurate to cell titers to about an OD of 0.6. The relationship between OD and cell titer depends on the configuration of the spectrophotometer, the length of the light path through the culture, the size of the bacterial cells, and the cell culture density. We demonstrate the importance of plate reader calibration to identify the exact relationship between OD and cells/ml. We use four bacterial genera and two sizes of micro-titer plates (96-well and 384-well) and show that the cell/ml per unit OD depends heavily on the bacterial cell size and plate size. We applied our calibration curve to real growth curve data and conclude the cells/ml - rather than OD - is a metric that can be used to directly compare results across experiments, labs, instruments, and species.

category: microbiology


title: Copper Acts Synergistically with Fluconazole in Candida glabrata by Compromising Drug Efflux, Sterol Metabolism, and Zinc Homeostasis

abstract:
The synergistic combinations of drugs are promising strategies to boost the effectiveness of current antifungals and thus prevent the emergence of resistance.

In this work, we show that copper and the antifungal fluconazole act synergistically against Candida glabrata, an opportunistic pathogenic yeast intrinsically tolerant to fluconazole.

Analyses of the transcriptomic profile of C. glabrata after the combination of copper and fluconazole showed that the expression of the multidrug transporter gene CDR1 was decreased, suggesting that fluconazole efflux could be affected. In agreement, we observed that copper inhibits the transactivation of Pdr1, the transcription regulator of multidrug transporters and leads to the intracellular accumulation of fluconazole. Copper also decreases the transcriptional induction of ergosterol biosynthesis (ERG) genes by fluconazole, which culminates in the accumulation of toxic sterols. Co-treatment of cells with copper and fluconazole should affect the function of proteins located in the plasma membrane, as several ultrastructural alterations, including irregular cell wall and plasma membrane and loss of cell wall integrity, were observed. Finally, we show that the combination of copper and fluconazole downregulates the expression of the gene encoding the zinc-responsive transcription regulator Zap1, which possibly, together with the membrane transporters malfunction, generates zinc depletion. Supplementation with zinc reverts the toxic effect of combining copper with fluconazole, underscoring the importance of this metal in the observed synergistic effect.

Overall, this work, while unveiling the molecular basis that supports the use of copper to enhance the effectiveness of fluconazole, paves the way for the development of new metal-based antifungal strategies.


title: Coupled protein quality control during nonsense mediated mRNA decay

abstract: Translation of mRNAs containing premature termination codons (PTCs) can result in truncated protein products with deleterious effects. Nonsense-mediated decay (NMD) is a surveillance path-way responsible for detecting and degrading PTC containing transcripts. While the molecular mechanisms governing mRNA degradation have been extensively studied, the fate of the nascent protein product remains largely uncharacterized. Here, we use a fluorescent reporter system in mammalian cells to reveal a selective degradation pathway specifically targeting the protein product of an NMD mRNA. We show that this process is post-translational, and dependent on an intact ubiquitin proteasome system. To systematically uncover factors involved in NMD-linked protein quality control, we conducted genome-wide flow cytometry-based screens. Our screens recovered known NMD factors, and suggested a lack of dependence on the canonical ribosome-quality control (RQC) pathway. Finally, one of the strongest hits in our screens was the E3 ubiquitin ligase CNOT4, a member of the CCR4-NOT complex, which is involved in initiating mRNA degradation. We show that CNOT4 is involved in NMD coupled protein degradation, and its role depends on a functional RING ubiquitin ligase domain. Our results demonstrate the existence of a targeted pathway for nascent protein degradation from PTC containing mRNAs, and provide a framework for identifying and characterizing factors involved in this process.

category: molecular biology


title: Limited, but potentially functional translation of non-coding transcripts in the HEK293T cellular cytosol

abstract: Ribosome profiling has revealed translation outside of canonical coding sequences (CDSs) including translation of short upstream ORFs, long non-coding RNAs, overlapping ORFs, ORFs in UTRs or ORFs in alternative reading frames. Studies combining mass spectrometry, ribosome profiling and CRISPR-based screens showed that hundreds of ORFs derived from non-coding transcripts produce (micro)proteins, while other studies failed to find evidence for such types of non-canonical translation products. Here, we attempted to discover translation products from non-coding regions by strongly reducing the complexity of the sample prior to mass spectrometric analysis. We used an extended database as the search space and applied stringent filtering of the identified peptides to find evidence for novel translation events. Theoretically, we show that our strategy facilitates the detection of translation events of transcripts from non-coding regions, but experimentally only find 19 peptides (less than 1% of all identified peptides) that might originate from such translation events. Virotrap based interactome analysis of two N-terminal proteoforms originating from non-coding regions finally showed the functional potential of these novel proteins.


title: Intramolecular interactions enhance the potency of gallinamide A analogs against Trypanosoma cruzi

abstract: Gallinamide A, a metabolite of the marine cyanobacterium Schizothrix sp., selectively inhibits cathepsin L-like cysteine proteases. We evaluated potency of gallinamide A and 23 synthetic analogs against intracellular Trypanosoma cruzi amastigotes and the cysteine protease, cruzain. We determined the co-crystal structures of cruzain with gallinamide A and two synthetic analogs at [~]2[A]. SAR data revealed that the N-terminal end of gallinamide A is loosely bound and weakly contributes in drug-target interactions. At the C-terminus, the intramolecular {pi}-{pi} stacking interactions between the aromatic substituents at P1 and P1 restrict the bioactive conformation of the inhibitors, thus minimizing the entropic loss associated with target binding. Molecular dynamics simulations showed that in the absence of an aromatic group at P1, the substituent at P1 interacts with tryptophan-184. The P1-P1 interactions had no effect on anti-cruzain activity whereas anti-T. cruzi potency increased by [~]5-fold, likely due to an increase in solubility/permeability of the analogs.


title: High-fidelity Cas13 variants for targeted RNA degradation with minimal collateral effect

abstract: CRISPR-Cas13 systems have recently been employed for targeted RNA degradation in various organisms. However, collateral degradation of bystander RNAs has imposed a major barrier for their in vivo applications. We designed a dual-fluorescent reporter system for detecting collateral effects and screening Cas13 variants in mammalian cells. Among over 200 engineered variants, several Cas13 variants (including Cas13d and Cas13X) exhibit efficient on-target activity but markedly reduced collateral activity. Furthermore, transcriptome-wide off-targets and cell growth arrest induced by Cas13 are absent for these variants. Importantly, high-fidelity Cas13 variants show comparable RNA knockdown activity with wild-type Cas13 but no detectable collateral damage in transgenic mice and adeno-associated virus-mediated somatic cell targeting. Thus, high-fidelity Cas13 variants with minimal collateral effect are now available for targeted degradation of RNAs in basic research and therapeutic applications.


title: Liquid-liquid phase separation facilitates the biogenesis of secretory storage granules

abstract:
Insulin is a key regulator of human metabolism, and its dysfunction leads to diseases such as type 2 diabetes. It remains unknown how proinsulin is targeted from the trans-Golgi network (TGN) to secretory storage granules as no cargo receptor has been identified. Chromogranin proteins (CGs) are central regulators of granule biosynthesis, and it was proposed that their aggregation is critical for this process. However, the molecular mechanism by which these molecules facilitate sorting at the TGN is poorly understood. Here, we show that CGs undergo liquid-liquid phase separation (LLPS) at low pH independently of divalent cations, such as calcium. Liquid CG condensates, but not aggregates, recruit and sort proinsulin and other granule-destined cargo molecules towards secretory granules. Cargo selectivity is independent of sequence or structural elements but is based on the size and concentration of the client molecules at the TGN. Finally, electrostatic interactions and the N-terminal intrinsically disordered domain of chromogranin B facilitate LLPS and are critical for granule formation. We propose that phase-separated CGs act as a "cargo sponge" within the TGN lumen, gathering soluble client proteins into the condensate independently of specific sequence or structural elements, facilitating receptor-independent sorting. These findings challenge the canonical TGN sorting models and provide insights into granule biosynthesis in insulin-secreting {beta}-cells.

One sentence summaryLiquid Chromogranin condensates recruit cargo molecules at the TGN for their delivery to secretory storage granules.

category: cell biology


title: Continental-scale Hyperspectral tree species classification in the National Ecological Observatory Network

abstract: Advances in remote sensing imagery and computer vision applications unlock the potential for developing algorithms to classify individual trees from remote sensing at unprecedented scales. However, most approaches to date focus on site-specific applications and a small number of taxonomic groups. This limitation makes it hard to evaluate whether these approaches generalize well across broader geographic areas and ecosystems. Leveraging field surveys and hyperspectral remote sensing data from the National Ecological Observatory Network (NEON), we developed a continental extent model for tree species classification that can be applied to the entire network including a wide range of US terrestrial ecosystems. We compared the performance of the generalized approach to models trained at each individual site, evaluating advantages and challenges posed by training species classifiers at the US scale. We evaluated the effect of geography, environmental, and ecological conditions on the accuracy and precision of species predictions. On average, the general model resulted in good overall classification accuracy (micro-F1 score), with better accuracy than site-specific classifiers (average individual tree level accuracy of 0.77 for the general model and 0.72 for site-specific models). Aggregating species to the genus-level increased accuracy to 0.83. Regions with more species exhibited lower classification accuracy. Trees were more likely to be confused with congeneric and co-occurring species and confusion was highest for trees with structural damage and in complex closed-canopy forests. The model produced accurate estimates of uncertainty, correctly identifying trees where confusion was likely. Using only data from NEON this single integrated classifier can make predictions for 20% of all tree species found in forest ecosystems across the US, suggesting the potential for broad scale general models for species classification from hyperspectral imaging.

category: ecology


title: Blue and green food webs respond differently to elevation and land use

abstract: While aquatic (blue) and terrestrial (green) food webs are parts of the same landscape, it remains unclear whether they respond similarly to shared environmental gradients. We use empirical community data from hundreds of sites across Switzerland, and show that blue and green food webs have different structural and ecological properties along elevation as a temperature proxy, and among various land-use types. Specifically, in green food webs, their modular structure increases with elevation and the overlap of consumers diet niche decreases, while the opposite pattern is observed in blue food webs. Such differences between blue and green food webs are particularly pronounced in farmland-dominated habitats, indicating that anthropogenic habitat modification moderates the climatic effects on food webs but differently in blue versus green systems. These findings indicate general structural differences between blue and green food webs and suggest their potential divergent future alterations through land use or climatic changes.


title: Life-stage and sex influence Philornis ectoparasitism in a Neotropical woodpecker (Melanerpes striatus) with essential male parental care

abstract: The nestlings of many Neotropical bird species suffer from Philornis (Diptera: Muscidae) ectoparasitism. While nestlings are typically considered the intended targets, recent work indicates that Philornis infest adult birds more frequently than previously appreciated, yet few studies have concurrently surveyed nestlings and adults for Philornis in the same population. Over six field seasons (2012-2017), I documented the presence of current or recent subcutaneous Philornis infestations on adult and nestling Hispaniolan Woodpeckers Melanerpes striatus from the same population. I tested the following three non-mutually exclusive hypotheses regarding occurrence of Philornis on adult birds: (1) nestlings are more vulnerable to Philornis parasitism than adults, (2) nesting is associated with Philornis parasitism in adults, and (3) Philornis parasitism is associated with incubation and brooding investment. While nestling and adult woodpeckers exhibited similar prevalence of parasitism, parasitized nestlings hosted on average 3.5 times more Philornis wounds (larvae plus empty wounds) than parasitized adults. Nesting per se was not significantly associated with parasitism among adults, as breeding and non-breeding adults showed similar prevalence and intensity. However, adult males, which perform overnight incubation and brooding, were significantly more likely to be parasitized than adult females. This last result supports the hypothesis that incubation and brooding investment increase the risk of Philornis parasitism for adults, but this conclusion is complicated by the lack of an association between parasitism and nesting status. Together, these results raise questions about the degree of host life-stage specialization and whether adult parasitism is incidental or part of an alternative parasitic strategy for Philornis.


title: On the assessment of the sources of inoculum of bacterial wilt in Brazil.

abstract: Dispersal of Ralstonia spp. cells by water and contaminated plant material and the importance of weeds as inoculum sources have been poorly investigated. Water of rivers, soil from fields of diverse crops and areas of natural vegetation both from the Amazonia, Cerrado and Mata Atlantica biomes, besides soil of the rhizosphere of weeds present in tomato fields with records of bacterial wilt were sampled and analyzed to detect Ralstonia spp. Seeds of tomato plants artificially and naturally infected with Ralstonia spp. were also processed. All samples were enriched a priori in selective medium South Africa (SMSA) and colonies were isolated in plates containing solid SMSA. Detection of Ralstonia spp. was confirmed by polymerase chain reaction with specific primers. The Co - operational PCR (CO-PCR) was also used to detect Ralstonia spp. Colonies were obtained from soil samples and from a commercial substrate sample. Five soil samples from eggplant fields, one from coffee field, one substrate from potato seed tuber production, two soil samples from the rhizosphere of Amaranthus spp., one from Bidens pilosa and one from Solanum americanum tested positive for Ralstonia spp. Besides these soil samples, five water samples of rivers were positive for CO-PCR detection: two samples from Amazonia, one from Cerrado and two samples from irrigation water collected from tomato fields located in the Mata Atlantica biome. Ralstonia spp. were not detected in tomato seeds. These results revealed potential inoculum sources, especially weeds, in areas with historical records of bacterial wilt. Additionally, rivers may act as dispersal agents of inoculum of Ralstonia spp.


title: Comparison of Three Individual Identification Algorithms for Sperm Whales (Physeter macrocephalus) after Automated Detection

abstract: Photo-identification of individual sperm whales (Physeter macrocephalus) is the primary technique for mark-recapture-based population analyses for the species The visual appearance of the fluke -- with its distinct nicks and notches -- often serves as the primary visual differentiator, allowing humans to make recorded sightings of specific individuals. However, the advent of digital photography and the significant increase in volume of images from multiple projects in combination with pre-existing historical catalogs has made applying the method more challenging.with the required human labor for de-duplication (reduction of Type II errors) and reconciliation of sightings between large datasets too cost- and time-prohibitive. To address this, we trained and evaluated the accuracy of PIE v2 (a triplet loss network) along with two existing fluke trailing edge-matching algorithms, CurvRank v2 and Dynamic Time Warping (DTW), as a mean to speed comparison among a high volume of photographs. Analyzed data were collected from a curated catalog of well-known sperm whales sighted across years (2005-2018) off the island of Dominica. The newly-trained PIE model outperformed the older CurvRank and DTW algorithms, and PIE provided the following top-k individual ID matching accuracy on a standard min-3/max-10 sighting training data set: Rank-1: 87.0%, Rank-5: 90.5%, and Rank-12: 92.5%. An essential aspect of PIE is that it can learn new individuals without network retraining, which can be immediately applied in the presence of (and for the resolution of) duplicate individuals in overlapping catalogs. Overall, our results recommend the use of PIE v2 and CurvRank v2 for ID reconciliation in combination due to their complementary performance.