bluuebunny/crossref_metadata_2025 huggingface dataset:
Environmental DNA concentrations of Japanese eels in relation to habitat characteristics
Authors: Ono Yurika , Hirasaka Katsuya , Myosho Taijun , Fujimoto Shingo , Yagi Mitsuharu
Published: October 2022

The Japanese eel (Anguilla japonica), is listed as “Endangered” by the IUCN. Understanding eel riverine habitat is useful in considering conservation strategies. This study sought to determine the relationship between environmental DNA (eDNA) concentrations derived from Japanese eels, water quality, and river structure in three small rivers in Nagasaki, Japan. eDNA was detected at 14 of 15 sites (93%). The concentration of eDNA in brackish water was significantly higher than that in freshwater and was correlated with water depth. Eel occurrence throughout the river suggests a need to conserve a diversity of habitats.
Task-based attentional and default mode connectivity associated with STEM anxiety profiles among university physics students
Authors: Smith Donisha D. , Meca Alan , Bottenhorn Katherine L. , Bartley Jessica E. , Riedel Michael C. , Salo Taylor , Peraza Julio A. , Laird Robert W. , Pruden Shannon M. , Sutherland Matthew T. , Brewe Eric , Laird Angela R.
Published: October 2022

Attentional control theory (ACT) posits that elevated anxiety increases the probability of re-allocating cognitive resources needed to complete a task to processing anxiety-related stimuli. This process impairs processing efficiency and can lead to reduced performance effectiveness. Science, technology, engineering, and math (STEM) students frequently experience STEM-related anxiety, which can interfere with learning and performance and negatively impact student retention and graduation rates. The objective of this study was to extend the ACT framework to investigate the neurobiological associations between STEM-related anxiety and cognitive performance among 123 physics undergraduate students. Latent profile analysis (LPA) identified four profiles of student STEM-related anxiety, including two profiles that represented the majority of the sample (Low STEM Anxiety; 59.3% and High Math Anxiety; 21.9%) and two additional profiles that were not well represented (High STEM Anxiety; 6.5% and High Science Anxiety; 4.1%). Students underwent a functional magnetic resonance imaging (fMRI) session in which they performed two tasks involving physics cognition: the Force Concept Inventory (FCI) task and the Physics Knowledge (PK) task. No significant differences were observed in FCI or PK task performance between High Math Anxiety and Low STEM Anxiety students. During the three phases of the FCI task, we found no significant brain connectivity differences during scenario and question presentation, yet we observed significant differences during answer selection within and between the dorsal attention network (DAN), ventral attention network (VAN), and default mode network (DMN). Further, we found significant group differences during the PK task were limited to the DAN, including DAN-VAN and within-DAN connectivity. These results highlight the different cognitive processes required for physics conceptual reasoning compared to physics knowledge retrieval, provide new insight into the underlying brain dynamics associated with anxiety and physics cognition, and confirm the relevance of ACT theory for STEM-related anxiety.
Kleptocytosis: A Novel Parasitic Strategy for Accelerated Reproduction via Host Protein Stealing in Varroa destructor
Authors: Ramsey Samuel D. , Cook Steven C. , Gulbronson Connor , vanEngelsdorp Dennis , Evans Jay , Posada Francisco , Sonenshine Daniel
Published: October 2022

The rapid reproductive capacity of Varroa destructor is among the most significant adaptations underpinning its success as a parasite. To exploit their honey bee host, the parasite must rapidly produce offspring that fully develop into adults and mate in an inflexible 9-day window. Inability to meet this deadline brings the foundress mite’s fitness to zero establishing heavy evolutionary pressure to accelerate reproduction & subsequent development of offspring. Our work fills in gaps in our understanding of a key pathway in this process. Varroa have a poorly-understood ability to pass heretofore unidentified host proteins through their body with minimal digestion/degradation. Via Native-PAGE, we were able to confirm that nine proteins shared with honey bee fat body tissue accumulate intact in the eggs of the foundress mite. As such, we hypothesized that the proteins were several egg yolk precursors synthesized and stored in the fat body. Using antibodies raised against honey bee vitellogenin (Vg) we positively identified this egg yolk precursor via SDS-PAGE and subsequent Western Blot. We then analyzed samples of honey bee fat body tissue, gravid Varroa, so called “phoretic” Varroa, and Varroa eggs via HPLC MS/MS to identify the remaining host proteins and determine their relative abundance. We detected egg yolk precursors in the large lipid transfer protein superfamily, in addition to hexamerin storage proteins, and miscellaneous motor/transfer proteins integral to embryonic development (transferrin, myosin heavy chain, and heat shock protein 60). Varroa lack the capacity to produce some of these proteins and instead employ kleptoparasitism on a molecular level to provision their developing ova, a pathway not described in any other host/parasite relationship, hereafter referred to as kleptocytosis. These different families of proteins are normally produced by the female and conveyed to the vitellogenic egg cell through protein specific receptor-mediated pathways. Such pathways would exclude foreign proteins. We hypothesize that the need to rely on a receptor-mediated pathway is circumvented via the specialized nutritive reproductive tissue, the lyrate organ. Through microCT imaging we detail the connection between the developing ovum and this dual-lobed organ. Better understanding of this pathway presents a novel target for Varroa management as the treatment need only accomplish slowing acquisition or deposition of host proteins thereby disrupting the mite’s ability to meet the temporal demand of its host.
Common brain areas for processing physiologically and socially ‘needed’ stimuli
Authors: Bosulu J. , Luo Y. , Hétu S.
Published: October 2022

We looked at the overlap between brain areas related to perception of physiologically and socially (non-physiological) needed stimuli and how they might regulate serotonin levels. First, we conducted separate ALE meta-analyses on published results pertaining to brain activation patterns when participants perceived food while hungry or water while thirsty, and social interactions while being excluded. This allowed us to identify common consistent brain activation patterns for physiological and social needed stimuli. We also looked at significant spatial association between the common network and serotonin receptor distribution. We found that regions within the mid-posterior insula, the anterior cingulate cortex and the caudate are at the intersection of physiological (hunger and thirst) and social (exclusion) aspects of ‘needing’. Furthermore, we found a significant positive spatial correlation between that common network and 5HT4 receptor among serotonin receptors. While this was the highest for serotonin receptors, it was not the highest of all receptors. Our study suggests there is a common brain pattern during the processing of physiologically and socially needed stimuli, and discusses their spatial association with serotonin receptors and its possible implication.
Phenotypic cross-species conservation and cross-generation directionality switching in epigenetic inheritance
Authors: Bhalla Ameek , Sharma Abhay
Published: October 2022

Evidence supporting non-DNA sequence-based inheritance in animals has increasingly been described in recent years, often under short-term, intergenerational inheritance or longer, transgenerational epigenetic inheritance (TEI). Existence of the latter, a stronger indicator of germline transmission, though established in invertebrates remains controversial in mammals due to inherent confounding factors. Besides evolutionary conservation, physiological implications of TEI also remain unclear. Leveraging invertebrate evidence of TEI to assess possible instances in mammals, and dissecting already described models to gain further insights are suggested approaches to address uncertainties in non-genetic inheritance. Here, in an unbiased approach, we compared existing transcriptomic data associated with so far available Drosophila models of inter- and trans-, and rodent models of inter-generational inheritance, observed phenotypic cross-species conservation and cross-generation directionality shift therein, and confirmed these observations experimentally in flies. Specifically, previous models of cold and diet induced inheritance in both flies and mice were commonly associated with altered regulation of proteolysis genes. Besides, fly TEI models were in general characterized by opposite phenotypic regulation between inter- and trans-generational offspring. As insulin producing cell (IPC) ablation was also associated with proteolysis gene dysregulation in one of the mouse models, we opted to use genetic ablation of IPCs in flies for the experimental confirmation. Remarkably, the ablation led to transcriptomic alterations across multiple generations, with dysregulated genes showing proteolysis enrichment. Similarly, phenotypic directionality changed in the opposite direction in transgenerational offspring of IPC ablated ancestors. These results support mammalian existence, and physiologically adaptive and maladaptive consequences of germline mediated epigenetic inheritance.
DeepAIR: a deep-learning framework for effective integration of sequence and 3D structure to enable adaptive immune receptor analysis
Authors: Zhao Yu , He Bing , Li Chen , Xu Zhimeng , Su Xiaona , Rossjohn Jamie , Song Jiangning , Yao Jianhua
Published: October 2022

Structural docking between the adaptive immune receptors (AIRs), including T cell receptors (TCRs) and B cell receptors (BCRs), and their cognate antigens is one of the most fundamental processes in adaptive immunity. However, current methods for predicting AIR-antigen binding largely rely on sequence-derived features of AIRs, omitting the structure features that are essential for binding affinity. In this study, we present a deep-learning framework, termed DeepAIR, for the accurate prediction of AIR-antigen binding by integrating both sequence and structure features of AIRs. DeepAIR consists of three feature encoders (a trainable-embedding-layer-based gene encoder, a transformer-based sequence encoder, and a pre-trained AlphaFold2-based structure encoder), a gating-based attention mechanism to extract important features, and a tensor fusion mechanism to integrate obtained features. We train and evaluate DeepAIR on three downstream prediction tasks, including the prediction of AIR-antigen binding affinity, the prediction of AIR-antigen binding reactivity, and the classification of the immune repertoire. On five representative datasets, DeepAIR shows outstanding prediction performance in terms of AUC (area under the ROC curve) in predicting the binding reactivity to various antigens, as well as the classification of immune repertoire for nasopharyngeal carcinoma (NPC) and inflammatory bowel disease (IBD). DeepAIR is freely available for academic purposes at https://github.com/TencentAILabHealthcare/DeepAIR. We anticipate that DeepAIR can serve as a useful tool for characterizing and profiling antigen binding AIRs, thereby informing the design of personalized immunotherapy.

Highlights

Integrating predicted AIR structures using AlphaFold2 significantly improves the prediction accuracy of the binding reactivity between AIRs and antigens.

DeepAIR is featured by a novel deep learning architecture that leverages both the gating-based attention mechanism and tensor fusion mechanism to effectively extract and integrate informative features from three feature encoders, including a trainable embedding-layer-based gene encoder, a transformer-based sequence encoder, and a pre-trained AlphaFold2-based structure encoder.

DeepAIR is implemented as a biologically interpretable deep learning framework that highlights the key residues in both α and β chains that are critical for predicting the AIR-antigen binding.
Fitness benefits from co-display favour subdominant male-male partnerships between phenotypes
Authors: Tolliver James D. M. , Kupán Krisztina , Lank David B. , Schindler Susanne , Küpper Clemens
Published: October 2022

Male-male competition over matings is a key driving force in the evolution of courtship. Typically, competition is an individual affair selecting for dominance and aggression. Yet, some males forgo direct confrontation and improve their reproductive success through cooperation. Occasionally, this leads to specialized alternative reproductive tactics that operate at the intersection of cooperation and conflict. We used a community game model, informed with empirical data derived from previous studies, to examine cooperation dynamics between lekking male ruffs (Calidris pugnax) using two different tactics: resident and satellite. Residents defend display courts against other residents on leks. In contrast, satellites forgo court defence and engage in cooperative co-display with selected residents. Co-displaying appears to alter female mate choice, yet the exact mechanism and consequences remain unclear. We modelled individual male mating success as a function of lek size, resident rank, and satellite competitiveness. Our most realistic model assumed that co-display draws copulations from residents proportional to the existing mating skew among them. Under this assumption, all residents benefit from co-display over single display when a satellite is on the lek, except for α-residents co-displaying with the most competitive satellites on large leks. Thus, satellites could nearly always choose their preferred co-display partner, but achieved the highest copulation rates with lower ranking (subdominant) residents on intermediate sized leks. Co-display between the satellite and lower ranking residents reduced the mating skew among residents. However, since copulations for satellites were similar over a range of potential co-display partners, a variety of co-displaying dyads is to be expected, which is consistent with observations in nature. We conclude that, given our model assumptions, co-displaying reduces the impact of male dominance on reproductive success and ultimately alters the course of sexual selection.
S100A4 plays a role in mouse arterial smooth muscle cell motility. Implication for intimal thickening formation
Authors: Cardoso dos Santos LM. , Klingelhöfer J. , Bochaton-Piallat ML.
Published: October 2022

During atherosclerosis, smooth muscle cells (SMCs) migrate and accumulate in the intima, where they switch from a contractile to a synthetic phenotype. This process is associated with decreased expression or loss of contractile proteins, such as α-smooth muscle actin (α-SMA) or smooth muscle myosin heavy chains (SMMHCs). We previously demonstrated that S100A4, a small calcium-binding protein, which exhibits intra- and extracellular functions, is a marker of the synthetic SMC phenotype. We have recently shown that neutralization of extracellular S100A4 in an ApoE knockout (KO) mouse model with established atherosclerotic lesions decreased the overall atherosclerotic burden. To explore the role of S100A4 in the accumulation of SMCs in the intima, we induced intimal thickening (IT) formation in full S100A4 knockout (KO) and wild type (WT) mice by completely ligating the left common carotid artery. With this model, we generated SMC-rich lesions. The deletion of S100A4 did not influence the size of the IT, neither its composition, as assessed by the expression of α-SMA and SMMHCs in S100A4 KO animals compared with WT animals, 4 weeks after ligation. Using primary cells isolated from both strains, we demonstrated that S100A4 KO SMCs were less prone to migrate than WT SMCs but they did not differ in their proliferative capacity. Our results indicate that S100A4 plays a role in SMC motility in vitro but its deletion does not influence IT formation in the mouse carotid artery ligation model.
A primary rodent triculture model to investigate the role of glia-neuron crosstalk in regulation of neuronal activity
Authors: Phadke Leela , Lau Dawn H. W. , Aghaizu Nozie D. , Ibarra Shania , Navarron Carmen M. , Granat Lucy , Magno Lorenza , Whiting Paul , Jolly Sarah
Published: October 2022

Neuroinflammation and hyperexcitability have been implicated in the pathogenesis of neurodegenerative disease, and new models are required to investigate the cellular crosstalk involved in these processes. We developed an approach to generate a quantitative and reproducible triculture system that is suitable for pharmacological studies. While primary rodent cells were previously grown in a coculture medium formulated to support only neurons and astrocytes, we now optimised a protocol to generate tricultures containing neurons, astrocytes and microglia by culturing in a medium designed to support all three cell types and adding exogenous microglia to cocultures. Immunocytochemistry was used to confirm the intended cell types were present. The percentage of ramified microglia in the tricultures decreases as the number of microglia present increases. Multi-electrode array (MEA) recordings indicate that microglia in the triculture model suppress neuronal activity in a dose-dependent manner. Neurons in both cocultures and tricultures were responsive to the potassium channel blocker 4-aminopyridine (4-AP) suggesting that neurons remained viable and functional in the triculture model. Furthermore, suppressed neuronal activity in tricultures correlated with decreased densities of dendritic spines and of the postsynaptic protein Homer1 along dendrites, indicative of a direct or indirect effect of microglia on synapse function.

We thus present a functional triculture model, which, due to its more complete cellular composition, is a more relevant model than standard cocultures. The model can be used to probe glia-neuron interactions and subsequently aid the development of assays for drug discovery, using neuronal excitability as a functional endpoint.
Comparison between ribosomal assembly and machine learning tools for microbial identification of organisms with different characteristics
Authors: Chau Stephanie , Rojas Carlos , Jetcheva Jorjeta G. , Markart Mary , Vijayakumar Sudha , Yuan Sophia , Stowbunenko Vincent , Shelton Amanda N. , Andreopoulos William B.
Published: October 2022

Genome assembly tools are used to reconstruct genomic sequences from raw sequencing data, which are then used for identifying the organisms present in a metagenomic sample. More recently, machine learning approaches have been applied to a variety of bioinformatics problems, and in this paper, we explore their use for organism identification. We start out by evaluating several commonly used metagenomic assembly tools, including PhyloFlash, MEGAHIT, MetaSPAdes, Kraken2, Mothur, UniCycler, and PathRacer, and compare them against state-of-the art deep learning-based machine learning classification approaches represented by DNABERT and DeLUCS, in the context of two synthetic mock community datasets. Our analysis focuses on determining whether ensembling metagenome assembly tools with machine learning tools has the potential to improve identification performance relative to using the tools individually. We find that this is indeed the case, and analyze the level of effectiveness of potential tool ensembling for organisms with different characteristics (based on factors such as repetitiveness, genome size, and GC content).

Author Summary

Metagenomic studies focus on the challenging problem of identifying the presence and abundance of different species in a sample. This process typically involves the creation of digital reads from the sample which correspond to small parts of the genome sequence, and then have to be assembled together by a genome assembly tool. More recently, machine learning approaches have been applied to a variety of bioinformatics problems, and in this paper, we explore their use for organism identification, and how they might complement traditional bioinformatics approaches. We conduct experiments with two representative state-of-the-art machine learning approaches and six metagenomic assembly tools in the context of two synthetic datasets. We find that for organisms with certain characteristics (levels of repetitiveness, GC content, and genome size), ensembling metagenome assembly tools with machine learning tools has the potential to improve species identification performance relative to using the tools individually.
Novel inductively-coupled ear-bars (ICEs) for fMRI signal enhancement in rat entorhinal cortex
Authors: Chen Yi , Fernandez Zachary , Zhu David C. , Counts Scott E. , Dorrance Anne M. , Yu Xin , Scheel Norman , Qian Wei , Gifani Mahsa , Qian Chunqi
Published: October 2022

Entorhinal cortex (EC) is a potential target of deep brain stimulation in Alzheimer’s disease (AD) and fMRI can enable whole-brain dynamic mapping noninvasively. However, it remains challenging to study EC-based fMRI connectivity in rodents due to image signal loss and the lower sensitivity of the surface coil ring or array coil for deep brain areas. To reduce the magnetic susceptibility artifacts driven signal loss issue, we introduced baby cream into the middle ear. To improve detection sensitivity, we implemented novel inductively-coupled ear-bars (ICEs) in the 7 T Bruker scanner, which resulted in an approximately 2-fold signal-to-noise ratio (SNR) increase in EC over the conventional surface array. The ICE can be conveniently utilized as an add-on device, with no modulation to the scanner interface. To demonstrate the applicability of ICEs for both task and resting-state (rs) fMRI, whole-brain echo-planar imaging (EPI) was performed in anesthetized rats modeling AD mixed dementia. Seed-based rs-fMRI connectivity maps emanating from the left entorhinal cortex demonstrated its connectivity to the hippocampus, piriform cortex, septal nuclei, and prefrontal cortex. Hence, this work demonstrates an optimized procedure for ICE by acquiring large scale networks emanating from a seed region that was not easily accessible by conventional MRI detectors, enabling better observation of EC-based brain fMRI connectivity studies with a higher signal-to-noise ratio in rodent models of dementia.
Prior unsupervised experience leads to long lasting effects in sensory gating during discrimination learning
Authors: de Hoz Livia , Barniv Dana , Nelken Israel
Published: October 2022

As the animal moves in its environment, the brain detects and learns the structure of the surrounding stimuli, independently of the immediate relevance this has for the animal. This experience influences subsequent learning in a manner quantified using paradigms such as latent inhibition or stimulus preconditioning, which measure the effect that unsupervised (not-reinforced) learning has on subsequent reinforced learning. Despite our understanding of the behavioural consequences of prior neutral experience, there is little understanding about the influence of this previous experience on neuronal plasticity. Using latent inhibition, we have shown in mice that learning a two tone discrimination is slower in mice that have had previous neutral exposure to the same or similar tones (<2/3 octave away). Neutral exposure thus elicits profound changes in the brain that influence subsequent learning. To study how previous experience influences experience-dependent plasticity, and better understand the interactions between experience, learning, and plasticity, we recorded sound evoked responses in the auditory cortex of exposed and trained mice. We studied both changes in response magnitude and changes in sensory dynamics, and related both to the differential behavioral effects of different pre-exposure conditions. Here we describe the neuronal changes that paralleled the behavioral findings. We found that discrimination learning led to stronger initial sound-evoked responses and a long-lasting increase in response adaptation and an increase. The first effect was delayed in animals that showed latent inhibition, paralleling behavioural learning. Overall our data reveal that slow changes in behaviour that accompanied learning, paralleled the slow dynamics of experience-dependent plasticity in auditory cortex.
Neurodegenerative disease associated pathways in brain of the triple transgenic Alzheimer’s model are reversed in vivo following two weeks peripheral administration of fasudil
Authors: Killick Richard , Elliott Christina , Ribe Elena , Broadstock Martin , Ballard Clive , Aarsland Dag , Williams Gareth
Published: October 2022

The pan ROCK inhibitor fasudil acts as a vasodilator and has been used as a medication post cerebral stroke for the past 27 years in Japan and China. More recently, on the basis of the involvement of ROCK inhibition on synaptic function, neuronal survival and processes associated with neuroinflammation, it has been suggested that the drug may be repurposed for neurodegenerative diseases. Indeed, fasudil has demonstrated preclinical efficacy in many neurodegenerative disease models.

To facilitate an understanding of the wider biological processes at play due to ROCK inhibition in the context of neurodegeneration we performed a global gene expression analysis on the brains of Alzheimer’s disease model mice treated with fasudil via peripheral i.p injection. Our results show that fasudil tends to drive gene expression in a reverse sense to that seen in postmortem neurodegenerative disease brains. The results are most striking in terms of pathway enrichment analysis where pathways regulated in Alzheimer’s disease and by fasudil treatment are overwhelmingly regulated in opposite directions.

Thus, our results bolster the repurposing potential of fasudil by demonstrating an anti-neurodegenerative phenotype in a disease context and highlight the potential of in vivo transcriptional profiling of drug activity.
CiDRE+ M2c macrophages hijacked by SARS-CoV-2 cause COVID-19 severity
Authors: Mitsui Yuichi , Suzuki Tatsuya , Kuniyoshi Kanako , Inamo Jun , Yamaguchi Kensuke , Komuro Mariko , Watanabe Junya , Edamoto Mio , Li Songling , Kouno Tsukasa , Oba Seiya , Hosoya Tadashi , Koyama Shohei , Sakaguchi Nobuo , Standley Daron M. , Shin Jay W. , Akira Shizuo , Yasuda Shinsuke , Miyazaki Yasunari , Kochi Yuta , Kumanogoh Atsushi , Okamoto Toru , Satoh Takashi
Published: October 2022

Infection of the lungs with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) via the angiotensin I converting enzyme 2 (ACE2) receptor induces a type of systemic inflammation known as a cytokine storm. However, the precise mechanisms involved in severe coronavirus disease 2019 (COVID-19) pneumonia are unknown. Here, we show that interleukin-10 (IL-10) changed normal alveolar macrophages into ACE2-expressing M2c-type macrophages that functioned as spreading vectors for SARS-CoV-2 infection. The depletion of alveolar macrophages and blockade of IL-10 attenuated SARS-CoV-2 pathogenicity. Furthermore, genome-wide association and quantitative trait locus analyses identified novel mRNA transcripts in human patients, COVID-19 infectivity enhancing dual receptor (CiDRE), which has unique synergistic effects within the IL-10-ACE2 system in M2c-type macrophages. Our results demonstrate that alveolar macrophages stimulated by IL-10 are key players in severe COVID-19. Collectively, CiDRE expression levels are potential risk factors that predict COVID-19 severity, and CiDRE inhibitors might be useful as COVID-19 therapies.

Graphical abstract
History matters: thermal environment before, but not during wasp attack determines the efficiency of symbiont-mediated protection
Authors: Jones Jordan E. , Hurst Gregory D. D.
Published: October 2022

The outcome of natural enemy attack in insects is commonly impacted by the presence of defensive microbial symbionts residing within the host. Beyond their presence, the outcome of the interaction can also depend on genetic and environmental factors. The thermal environment is a key factor known to affect symbiont-mediated traits in insects, including their ability to defend against natural enemy attack. Cooler temperatures, for instance, have been previously shown to reduce Spiroplasma-mediated protection in Drosophila. Here, we dissect the effect of the thermal environment on Spiroplasma-mediated protection against Leptopilina boulardi in Drosophila melanogaster by examining the effect of temperature before, during and after wasp attack on fly survival and wasp success. We observed that the developmental temperature of the mothers’ of attacked larvae, and not the temperature of the attacked larvae themselves during or after wasp attack, strongly determines the protective influence of Spiroplasma. Spiroplasma-mediated fly survival was found to be weaker when parental flies were reared at 21°C before their larvae were exposed to wasps compared to larvae derived from parental flies reared at 23°C or 25°C. Contrastingly, there was no effect of thermal environment on protection when mothers were reared at 25°C, and their progeny exposed to lower temperatures during and after wasp attack. The effect of developmental temperature on Spiroplasma-mediated protection is likely mediated by reduced Spiroplasma titre combined, at cooler temperatures, with segregation of infection. These results indicate the historical thermal environment is a stronger determinant of protection than current environment, and that protective capacity is partly an epigenetic trait.
Homeostatic Control of Deep Sleep inDrosophila: Implications for Discovering Correlates of Sleep Pressure
Authors: Chowdhury Budhaditya , Abhilash Lakshman , Ortega Antonio , Liu Sha , Shafer Orie
Published: October 2022

Homeostatic control of sleep is typically addressed through mechanical stimulation-induced forced wakefulness and the measurement of subsequent increases in sleep. A major confound attends this approach: biological responses to deprivation may reflect a direct response to the mechanical insult rather than to the loss of sleep. Similar confounds accompany all forms of sleep deprivation and represent a major challenge to the field. Here we describe a new paradigm for sleep deprivation inDrosophilathat fully accounts for sleep-independent effects. Our results reveal that deep sleep states are the primary target of homeostatic control and establish the presence of multi-cycle sleep rebound following deprivation. Furthermore, we establish that specific deprivation of deep sleep state results in state-specific homeostatic rebound. Finally, by accounting for the molecular effects of mechanical stimulation during deprivation experiments, we show that serotonin levels track sleep pressure in the fly’s central brain. Our results illustrate the critical need to control for sleep-independent effects of deprivation when examining the molecular correlates of sleep pressure and call for a critical reassessment of work that has not accounted for such non-specific effects.
Crystal structure of monkeypox H1 phosphatase, an Antiviral Drug Target
Authors: Cui Wen , Huang Haojun , Duan Yinkai , Luo Zhi , Wang Haofeng , Zhang Tenan , Nguyen Henry , Shen Wei , Su Dan , Ji Xiaoyun , Yang Haitao , Wang Wei
Published: October 2022

The current monkeypox outbreak has caused over 64,000 global cases, but the effective treatments are very limited. The dual specific phosphatase (H1) from monkeypox antagonizes the immune response and is crucial for viral replication, making it an attractive antiviral target. Here we determined a 1.8-Å crystal structure of H1, which forms a domain swapped dimer resembling a butterfly. Each active site, which consists of a Cys-Arg-Asp triad, captures a phosphate ion. The observed conformation mimics the final step of catalysis prior to product release. The crystal structure provides a strong foundation for the discovery of new antivirals against this emerging worldwide pathogen.
Functional homologous recombination assay on FFPE specimens of advanced high-grade serous ovarian cancer predicts clinical outcomes
Authors: Pikkusaari Sanna , Tumiati Manuela , Virtanen Anni , Oikkonen Jaana , Li Yilin , Perez-Villatoro Fernando , Muranen Taru , Salko Matilda , Huhtinen Kaisa , Kanerva Anna , Koskela Heidi , Tapper Johanna , Koivisto-Korander Riitta , Joutsiniemi Titta , Haltia Ulla-Maija , Lassus Heini , Hautaniemi Sampsa , Färkkilä Anniina , Hynninen Johanna , Hietanen Sakari , Carpén Olli , Kauppi Liisa
Published: October 2022

Deficiency in homologous recombination (HR), a key DNA repair pathway, is a defining characteristic of many high-grade serous ovarian carcinomas (HGSC) and a major determinant of therapy outcomes. Patients with HR-deficient (HRD) tumors are more sensitive to DNA damaging platinum-based chemotherapy and HR deficiency also confers sensitivity to PARP inhibitors. While PARP inhibitors are highly effective in some patients, they are expensive and not without side effects, thus it is imperative to identify patients most likely to benefit from them. We set out to develop a clinically feasible assay for identifying functionally HRD tumors based on the detection of RAD51, a key HR protein. Our functional HR assay can be performed on FFPE tumor sample sections obtained from both treatment-naïve and neoadjuvant chemotherapy treated HGSC patients. We show that the functional HR test predicts key clinical outcomes, including platinum-free survival and overall survival after PARPi treatment. Our results indicate that RAD51-based HRD testing has great potential to predict platinum and PARPi sensitivity in the clinical setting.
Organization of reward and movement signals in the basal ganglia and cerebellum
Authors: Larry Noga , Zur Gil , Joshua Mati
Published: October 2022

The basal ganglia and the cerebellum are major subcortical structures in the motor system. The basal ganglia have been cast as the reward center of the motor system, whereas the cerebellum is thought to be involved in adjusting sensorimotor parameters. Recent findings of reward signals in the cerebellum have challenged this dichotomous view. To compare the basal ganglia and the cerebellum directly, we recorded from oculomotor regions in both structures from the same monkeys. We partitioned the trial-by-trial variability of the neurons into reward and eye-movement signals to compare the coding across structures. Reward expectation and movement signals were the most pronounced in the output structure of the basal ganglia, intermediate in the cerebellum, and the smallest in the input structure of the basal ganglia. These findings suggest that reward and movement information is sharpened through the basal ganglia, resulting in a higher signal-to-noise ratio than in the cerebellum.
SARS-CoV-2 spike protein induces endothelial dysfunction in 3D engineered vascular networks
Authors: Stern Brett , Monteleone Peter , Zoldan Janet
Published: October 2022

With new daily discoveries about the long-term impacts of COVID-19 there is a clear need to develop in vitro models that can be used to better understand the pathogenicity and impact of COVID-19. Here we demonstrate the utility of developing a model of endothelial dysfunction that utilizes induced pluripotent stem cell-derived endothelial progenitors encapsulated in collagen hydrogels to study the effects of COVID-19 on the endothelium. We found that treating these cell-laden hydrogels with SARS-CoV-2 spike protein resulted in a significant decrease in the number of vessel-forming cells as well as vessel network connectivity. Following treatment with the anti-inflammatory drug dexamethasone, we were able to prevent SARS-CoV-2 spike protein-induced endothelial dysfunction. In addition, we confirmed release of inflammatory cytokines associated with the COVID-19 cytokine storm. In conclusion, we have demonstrated that even in the absence of immune cells, we are able to use this 3D in vitro model for angiogenesis to reproduce COVID-19 induced endothelial dysfunction seen in clinical settings.
Signatures of Microbial Diversity at Multiple Scales of Resolution within Engineered Enrichment Communities
Authors: McDaniel Elizabeth A , Moya Francisco , Mendez Diana , Weathersby Coty , Oyserman Ben O , Flowers Jason , He Shaomei , Petriglieri Francesca , Singleton Caitlin , Nielsen Per H , McMahon Katherine D
Published: October 2022

Microbial community dynamics are dictated by both abiotic environmental conditions and biotic interactions. These communities consist of individual microorganisms across the continuum of phylogenetic diversity, ranging from coexisting members of different domains of life and phyla to multiple strains with only a handful of single nucleotide variants. Ecological forces act on a shifting template of population-level diversity that is shaped by evolutionary processes. However, understanding the ecological and evolutionary forces contributing to microbial community interactions and overall ecosystem function is difficult to interrogate for complex, naturally occurring microbial communities. Here, we use two time series of lab-scale engineered enrichment microbial communities simulating phosphorus removal to explore signatures of microbial diversity at multiple phylogenetic scales. We characterized microbial community dynamics and diversity over the course of reactor start-up and long-term dynamics including periods of eubiosis and dysbiosis as informed by the intended ecosystem function of phosphorus removal. We then compared these signatures to lineages from full-scale WWTPs performing phosphorus removal. We found that enriched lineages in lab-scale bioreactors harbor less intra-population diversity than lineages from the full-scale WWTP overall. Our work establishes a foundation for using engineered enrichment microbial communities as a semi-complex model system for addressing the fundamental ecological and evolutionary processes necessary for developing stable microbiome based biotechnologies.
Memory in Repetitive Protein–Protein Interaction Series – in Memory of the Late Professor Robert M. Nerem
Authors: Rosado Aaron M. , Zhang Yan , Choi Hyun-Kyu , Ehrlich Samuel M. , Jin Fengzhi , Grakoui Arash , Evavold Brian D. , Zhu Cheng
Published: October 2022

Over the past three decades, the senior author had interacted with and been mentored by the late Professor Robert M. Nerem. In his memory, the authors summarized several observations made, ideas conceptualized, and mathematical models developed during this period for quantitatively analyzing memory effects in repetitive protein–protein interactions (PPI). Interactions between proteins in an organism coordinate its biological processes and may impact its responses to changing environment and diseases through feedback systems. Feedback systems function by using changes in the past to influence behaviors in the future, which we refer here as memory. Specifically, we consider how proteins on cell or in isolation retain information about prior interactions to impact current interactions. The micropipette, biomembrane force probe and atomic force microscopic techniques were used to repeatedly assay several PPIs. The resulting time series were analyzed by a previous and two new models to extract three memory indices of short (seconds), intermediate (minutes), and long (hours) timescales. We found that interactions of cell membrane, but not soluble, T cell receptor (TCR) with peptide-major histocompatibility complex (pMHC) exhibits short-term memory that impacts on-rate, but not off-rate of the binding kinetics. Peptide dissociation from MHC resulted in intermediate- and long-term memories in TCR–pMHC interactions. However, we observed no changes in kinetic parameters by repetitive measurements on living cells over intermediate timescale using stable pMHCs. Parameters quantifying memory effects in PPIs could provide additional information regarding biological mechanisms. The methods developed herein also provide tools for future research.
Deformability Cytometry Clustering with Variational Autoencoders
Authors: Seith Daniel D. , Combs Cody , Siwy Zuzanna S.
Published: October 2022

Mechanobiology has shown great success in revealing complex cellular dynamics in various pathologies and physiologies. Most methods for assessing a cell’s mechanical properties, however, generally extract only a few physical constants such as Young’s modulus. This can limit the potential for accurate classification given the wide variety of rheological properties of cells, there are many ways for cells to differ. While it was recently shown that deep learning can classify cells more accurately than traditional approaches, it is not clear how this may be extended to unsupervised classification. In this work, we showcase the potential for a deep learning model to classify cells in an unsupervised fashion using a blend of physical properties. We introduce the combination of a variational autoencoder and a previously described clustering loss for classifying cells in an unsupervised fashion.
Contribution of 6mer seed toxicity to HIV-1 induced cytopathicity
Authors: Vaidyanathan Aparajitha , Taylor Harry E. , Hope Thomas J. , D’Aquila Richard T. , Bartom Elizabeth T. , Hultquist Judd F. , Peter Marcus E.
Published: October 2022

HIV-1 (HIV) infects CD4 positive T cells, the gradual depletion of which can lead to the onset of Acquired Immunodeficiency Syndrome (AIDS) in the absence of antiretroviral therapy (ART). Several forms of cell death have been shown to be involved in HIV-mediated killing of either directly infected or bystander cells. It is still unknown, however, why some cells survive HIV infection and persist as part of the latently infected reservoir that reliably causes recurrent viremia upon ART cessation. Improved understanding of the mechanisms of HIV-mediated cell death could inform innovations designed to clear the latent reservoir. “Death Induced by Survival gene Elimination” (DISE) is an RNA interference (RNAi)-based mechanism that kills cells through short (s)RNAs with toxic 6mer seeds (pos. 2-7 of sRNA). These toxic seeds target reverse complementary seed matches in the 3’UTR of mRNA transcripts to decrease expression of hundreds of genes that are critical for cell survival. In most cells under normal conditions, highly expressed cell-encoded non-toxic microRNAs (miRNAs) block access of toxic sRNAs to the RNA-induced silencing complex (RISC) that mediates RNAi, promoting cell survival. We now report that infection of cells with HIV results in RISC-loading of an HIV-encoded miRNA, v-miRNA HIV-miR-TAR-3p, which kills cells by DISE through a noncanonical (pos. 3-8) 6mer seed. In addition, cellular RISC bound sRNAs shift to lower seed viability. Both these effects also occur with latent HIV provirus reactivation in J-Lat cells, a well-established cell model of HIV latency. Cells lacking expression of miRNA biogenesis genes Drosha, Dicer and Exportin 5 cannot produce protective miRNAs and therefore do not block RISC loading of the v-miRNA HIV-miR-TAR-3p. These mutant cells, as well as cells lacking expression of the RISC component Ago2, are hypersensitive to cell death via DISE induced by HIV infection. More precise targeting of the balance between protective and cytotoxic sRNAs could specifically and transiently increase silencing of cell survival genes to increase DISE. This could be a new addition to a “shock and kill” strategy to enhance depletion of the provirus reservoir during suppressive ART.
Engineering a plant polyketide synthase for the biosynthesis of methylated flavonoids
Authors: Peng Bo , Zhang Lili , He Siqi , Oerlemans Rick , Quax Wim J. , Groves Matthew R. , Haslinger Kristina
Published: October 2022

Homoeriodictyol and hesperetin are naturally occurring O-methylated flavonoids with many health-promoting properties. They are produced in plants in low abundance and as complex mixtures of similar compounds that are difficult to separate. Synthetic biology offers the opportunity to produce various flavonoids in a targeted, bottom-up approach in engineered microbes with high product titers. However, the production of O-methylated flavonoids is currently still highly inefficient.

In this study, we investigated and engineered a combination of enzymes that had previously been shown to support homoeriodictyol and hesperetin production inEscherichia colifrom fed O-methylated cinnamic acids. We determined the crystal structures of the enzyme catalyzing the first committed step of the pathway, chalcone synthase fromHordeum vulgare, in three ligand-bound states. Based on these structures and a multiple sequence alignment with other chalcone synthases, we constructed mutant variants and assessed their performance inE. colitowards producing methylated flavonoids. With our best mutant variant, HvCHS (Q232P, D234V), we were able to produce homoeriodictyol and hesperetin at 2 times and 10 times higher titers than previously reported. Our findings will facilitate the further engineering of this enzyme towards higher production of methylated flavonoids.
DNA Modifications Enabling Proximity Biotinylation
Authors: Wilbanks Brandon , Pearson Keenan , Byrne Shane R. , Bickart Laura B. , Dedon Peter C. , Maher L. James
Published: October 2022

Advances in peroxidase- and biotin ligase-mediated signal amplification have enabled high-resolution subcellular mapping of endogenous RNA localization and protein-protein interactions. Application of these technologies has been limited to RNA and proteins because of the reactive groups required for biotinylation in each context. Here we report several novel methods for proximity biotinylation of exogenous oligodeoxyribonucleotides by application of well-established and convenient enzymatic tools. We describe approaches using simple and efficient conjugation chemistries to modify deoxyribonucleotides with “antennae” sensitive to phenoxy radical or biotinoyl-5’-adenylate. In addition, we report chemical details of a previously undescribed adduct between tryptophan and a phenoxy radical group. These developments have potential application in the selection of exogenous nucleic acids capable of unaided entry into living cells.
Basic Bacteriological Routines
Authors: Figueroa-Bossi Nara , Balbontín Roberto , Bossi Lionello
Published: October 2022

In experimental bacteriology, bacteria are generally manipulated, stored, and shipped in the form of cultures. Depending on various factors, including strain genotype, storage and shipping methods, and manipulator skills, the culture may contain genetic variants or simply contaminants. It is therefore important to begin an experiment by streaking the culture on an agar plate. Streaking, a technique to disperse bacterial cells on the surface of the agar, serves the purpose of isolating individual colonies. A colony originates from a single cell and is a nearly pure culture. On rich LB medium after 24 h of incubation at 37°C, a colony of Salmonella contains ∼5 × 108 cells (about 29 generations). Streaking is also required in experiments that themselves generate single colonies as a result of selection (e.g., when constructing strains or introducing plasmids). Except in the few instances in which the selection efficiently kills all counter-selected bacteria, colonies growing on the selective plates are contaminated, sometimes heavily, with cells from the bacterial lawn. “Purifying” the colonies arising in such experiments by streaking on selective plates is therefore a mandatory step. Here, we show how this can be conveniently done using simple toothpicks. We also briefly describe the steps involved in inoculating liquid cultures, spreading plates, and replica plating.