Towards a molecular mechanism underlying mitochondrial protein import through the TOM and TIM23 complexes Nearly all mitochondrial proteins need to be targeted for import from the cytosol. For the majority, the first port of call is the translocase of the outer membrane (TOM complex), followed by a procession of alternative molecular machines, conducting transport to their final destination. The pre-sequence translocase of the inner-membrane (TIM23-complex) imports proteins with cleavable pre-sequences, and comes in two flavours: the TIM23SORT complex mediates inner mitochondrial membrane (IMM) protein insertion and the TIM23MOTOR complex delivers proteins to the matrix. Progress in understanding these transport mechanisms has been hampered by the poor sensitivity and time-resolution of import assays. However, with the development of an assay based on split NanoLuc luciferase, we can now explore this process in greater detail. Here, we apply this new methodology to understand how {Delta}{psi} and ATP hydrolysis, the two main driving forces for import through the TIM23MOTOR complex, contribute to the import of pre-sequence-containing precursors (PCPs) with varying properties. Notably, we found that two major rate-limiting steps define PCP import time: passage of PCP across the OMM and initiation of IMM transport by the pre-sequence. The rates of these steps are influenced by PCP properties such as size and net charge, but not total amount of PCP imported - emphasising the importance of collecting rapid kinetic data, achieved here, to elucidate mechanistic detail. The apparent distinction between transport through the two membranes (passage through TOM is substantially complete before PCP-TIM engagement) is in contrast with the current view that import occurs through TOM and TIM in a single continuous step. Our results also indicate that PCPs spend very little time in the TIM23 channel - presumably rapid success or failure of import is critical for maintaining mitochondrial fitness.
Comparative proteome signatures of trace samples by multiplexed Data-Independent Acquisition Single cell transcriptomics has revolutionized our understanding of basic biology and disease. Since transcript levels often do not correlate with protein expression, it is crucial to complement transcriptomics approaches with proteome analyses at single cell resolution. Despite continuous technological improvements in sensitivity, mass spectrometry-based single cell proteomics ultimately faces the challenge of reproducibly comparing the protein expression profiles of thousands of individual cells. Here, we combine two hitherto opposing analytical strategies, DIA and Tandem-Mass-Tag (TMT)-multiplexing, to generate highly reproducible, quantitative proteome signatures from ultra-low input samples. While conventional, data-dependent shotgun proteomics (DDA) of ultra-low input samples critically suffers from the accumulation of missing values with increasing sample-cohort size, data-independent acquisition (DIA) strategies do usually not take full advantage of isotope-encoded sample multiplexing. We developed a novel, identification-independent proteomics data-analysis pipeline that allows to quantitatively compare DIA-TMT proteome signatures across hundreds of samples independent of their biological origin, and to identify cell types and single protein knockouts. We validate our approach using integrative data analysis of different human cell lines and standard database searches for knockouts of defined proteins. These data establish a novel and reproducible approach to markedly expand the numbers of proteins one detects from ultra-low input samples, such as single cells.
Diverse stem-chondrichthyan oral structures and evidence for an independently acquired acanthodid dentition The teeth of sharks famously form a series of transversely-organised files with conveyor-belt replacement that are borne directly on the jaw cartilages, in contrast to the dermal plate-borne dentition of bony fishes that undergoes site-specific replacement. A major obstacle in understanding how this system evolved is the poorly understood relationships of the earliest chondrichthyans and the profusion of morphologically and terminologically diverse bones, cartilages, splints and whorls that they possess. Here we use tomographic methods to investigate mandibular structures in several early branching  acanthodian-grade stem-chondrichthyans. We show that the dentigerous jaw bones of disparate genera of ischnacanthids are united by a common construction, being growing bones with non-shedding dentition. Mandibular splints, which support the ventro-lateral edge of the Meckels cartilage in some taxa, are formed from dermal bone and may be an acanthodid synapomorphy. We demonstrate that the teeth of Acanthodopsis are borne directly on the mandibular cartilage and that this taxon is deeply nested within an edentulous radiation, representing an unexpected independent origin of teeth. Many or even all of the range of unusual oral structures may be apomorphic, but they should nonetheless be considered when building hypotheses of tooth and jaw evolution, both in chondrichthyans and more broadly. Data-Driven Network Models for Genetic Circuits From Time-Series Data with Incomplete Measurements Synthetic gene networks are frequently conceptualized and visualized as static graphs. This view of biological programming stands in stark contrast to the transient nature of biomolecular interaction, which is frequently enacted by labile molecules that are often unmeasured. Thus, the network topology and dynamics of synthetic gene networks can be difficult to verify in vivo or in vitro, due to the presence of unmeasured biological states. Here we introduce the dynamical structure function as a new mesoscopic, data-driven class of models to describe gene networks with incomplete measurements. We introduce a network reconstruction algorithm and a code base for reconstructing the dynamical structure function from data, to enable discovery and visualization of graphical relationships in a genetic circuit diagram as time-dependent functions rather than static, unknown weights. We prove a theorem, showing that dynamical structure functions can provide a data-driven estimate of the size of crosstalk fluctuations from an idealized model. We illustrate this idea with numerical examples. Finally, we show how data-driven estimation of dynamical structure functions can explain failure modes in two experimentally implemented genetic circuits, a historical genetic circuit and a new E. coli based transcriptional event detector. Royal knifefish generate powerful suction feeding through large neurocranial elevation and high epaxial muscle power Suction feeding in ray-finned fishes involves powerful buccal cavity expansion to accelerate water and food into the mouth. Previous XROMM studies in largemouth bass (Micropterus salmoides), bluegill sunfish (Lepomis macrochirus), and channel catfish (Ictalurus punctatus) have shown that more than 90% of suction power in high performance strikes comes from the axial musculature. Thus, the shape of the axial muscles and skeleton may impact suction feeding mechanics. Royal knifefish (Chitala blanci) have an unusual postcranial morphology, with a ventrally flexed vertebral column and relatively large mass of epaxial muscle. Based on their body shape, we hypothesized that royal knifefish would generate high power strikes by utilizing large neurocranial elevation, vertebral column extension, and epaxial shortening. As predicted, C. blanci generated high suction expansion power compared to the other three species studied to date (up to 160 W), which was achieved by increasing both the rate of volume change and the intraoral subambient pressure. The large epaxial muscle (25% of body mass) shortened at high velocities to produce large neurocranial elevation and vertebral extension (up to 41 deg, combined), as well as high muscle mass-specific power (up to 800 W kg-1). For the highest power strikes, axial muscles generated 95% of the power, and 64% of the axial muscle mass consisted of the epaxial muscles. The epaxial-dominated suction expansion of royal knifefish supports our hypothesis that postcranial morphology may be a strong predictor of suction feeding biomechanics.

SUMMARY STATEMENTRoyal knifefish rely on their distinct postcranial morphology--with a curved vertebral column and large dorsal body muscles--to produce large neurocranial elevation and powerful suction feeding. Polycomb suppresses a female gene regulatory network to ensure testicular differentiation Gonadal sex determination is controlled by the support cells of testes and ovaries. In testes, the epigenetic mechanism that maintains cellular memory to suppress female sexual differentiation remains unknown. Here, we show that Polycomb suppresses a female gene regulatory network in Sertoli cells, the specific support cells for postnatal testes. Through genetic ablation, we removed Polycomb repressive complex 1 (PRC1) from embryonic Sertoli cells after sex determination. PRC1-depleted postnatal Sertoli cells exhibited defective proliferation and cell death, leading to the degeneration of adult testes. In adult Sertoli cells, PRC1 suppressed the specific, critical genes required for granulosa cells, the support cells of ovaries, thereby inactivating the female gene regulatory network. The underlying chromatin of female genes was coated with Polycomb-mediated repressive modifications: PRC1-mediated H2AK119ub and PRC2-mediated H3K27me3. Taken together, we identify a critical mechanism centered on Polycomb that maintains the male fate in adult testes. Platelet transcriptome yields progressive markers in chronic myeloproliferative neoplasms and identifies putative targets of therapy Predicting disease progression remains a particularly challenging endeavor in chronic degenerative disorders and cancer, thus limiting early detection, risk stratification, and preventive interventions. Here, profiling the spectrum of chronic myeloproliferative neoplasms (MPNs) as a model, we identify the blood platelet transcriptome as a proxy for highly sensitive progression biomarkers that also enables prediction of advanced disease via machine learning algorithms. Using RNA sequencing (RNA-seq), we derive disease-relevant gene expression in purified platelets from 120 peripheral blood samples constituting two time-separated cohorts of patients diagnosed with one of three MPN subtypes at sample acquisition - essential thrombocythemia, ET (n=24), polycythemia vera, PV (n=33), and primary or post ET/PV secondary myelofibrosis, MF (n=42), and healthy donors (n=21). The MPN platelet transcriptome reveals an incremental molecular reprogramming that is independent of patient driver mutation status or therapy and discriminates each clinical phenotype. Leveraging this dataset that shows a characteristic progressive expression gradient across MPN, we develop a machine learning model (Lasso-penalized regression) and predict advanced subtype MF at high accuracy and under two conditions of external validation: i) temporal: our two Stanford cohorts, AUC-ROC of 0.96; and ii) geographical: independently published data of an additional n=25 MF and n=46 healthy donors, AUC-ROC of 0.97). Lasso-derived signatures offer a robust core set of < 5 MPN transcriptome markers that are progressive in expression. Mechanistic insights from our data highlight impaired protein homeostasis as a prominent driver of MPN evolution, with persistent integrated stress response. We also identify JAK inhibitor-specific signatures and other interferon, proliferation, and proteostasis-associated markers as putative targets for MPN-directed therapy. Our platelet transcriptome snapshot of chronic MPNs demonstrates a proof of principle for disease risk stratification and progression beyond genetic data alone, with potential utility in other progressive disorders.

HighlightsLeveraging two independent and mutually validating MPN patient cohorts, we identify progressive transcriptomic markers that also enable externally validated prediction in MPNs.

Our platelet RNA-Seq data identifies impaired protein homeostasis as prominent in MPN progression and offers putative targets of therapy.

VISUAL ABSTRACT

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org.highwire.dtl.DTLVardef@72dc16org.highwire.dtl.DTLVardef@cf5096org.highwire.dtl.DTLVardef@b3d460org.highwire.dtl.DTLVardef@3c0ddc_HPS_FORMAT_FIGEXP  M_FIG C_FIG Single-cell phenotypic characteristics of tolerance under recurring antibiotic exposure in Escherichia coli. Non-heritable drug resistance, such as tolerance and persistence towards antibiotics, is little characterized compared to genetic resistance. Tolerance and persistence allow cells to survive application of antibiotics that are bactericidal to non-tolerant cells. Non-heritable drug resistance challenges antibiotic treatment, particularly of recurrent infections, and have implications towards heritable resistance evolution. Tolerant cells have commonly been characterized as growth arrested cells prior and during antibiotic application that quickly resume growth post-application. Here, we explore characteristic of tolerant and susceptible E. coli single bacteria cells to different levels of recurrent antibiotic exposure and quantify their occurrence. In using a high throughput single-cell microfluidic device, we find that tolerant cells reduce their growth rate by about 50%, but contrary to previous findings do not go into growth arrest or near growth arrest. The growth reduction is induced by antibiotic exposure and not caused by a stochastic switch or predetermined state as previously described. Cells exhibiting constant intermediate growth survived best under antibiotic exposure and selection did not primarily act on fast growing cells, as expected for a {beta}-lactam antibiotic. Control experiments on population cultures confirmed and challenged scaling of single cell findings to population level processes. Our findings suggest a prevalent type of tolerance that differs from previously described tolerance and persister characteristics. Our described characteristics and its high frequency of occurrence supports acclaims of an underappreciated role of tolerant cells towards resistance evolution.

Author SummaryResistance to antibiotics is a major cause of treatment failure in modern medicine. In addition to genetic resistance, bacterial cells can sustain periods of bactericidal application in a so-called tolerant state. Previously tolerant cells were characterized by growth arrest prior and during exposure to antibiotics. Here, we show a distinctive type of tolerance that arises out of normally growing cells, where during antibiotic exposure, cell growth is slowed but does not go into growth arrest. Cells with an intermediate growth have the best survival, which is contrary to the assumptions of exposure to a {beta}-lactam antibiotic where selection is assumed to act against the fastest growing cells and the least against non-growing cells. The novel characteristics of tolerance that we have uncovered provides bacteria with another route to evade antibiotics and that could be a considerable threat to the efficiency of antibiotic treatment. New Segmentation and Feature Extraction Algorithm for Classification of White Blood Cells in Peripheral Smear Images This article addresses a new method for the classification of white blood cells (WBCs) using image processing techniques and machine learning methods. The proposed method consists of three steps: detecting the nucleus and cytoplasm, extracting features, and classification. At first, a new algorithm is designed to segment the nucleus. For the cytoplasm to be detected, only a part of it located inside the convex hull of the nucleus is involved in the process. This attitude helps us overcome the difficulties of segmenting the cytoplasm. In the second phase, three shapes and four novel color features are devised and extracted. Finally, by using an SVM model, the WBCs are classified. The segmentation algorithm can detect the nucleus with a dice similarity coefficient of 0.9675. The proposed method can categorize WBCs in Raabin-WBC, LISC, and BCCD datasets with accuracies of 94.65 %, 92.21 %, and 94.20 %, respectively. It is worth mentioning that the hyperparameters of the classifier are fixed only with the Raabin-WBC dataset, and these parameters are not readjusted for LISC and BCCD datasets. The obtained results demonstrate that the proposed method is robust, fast, and accurate. Nuclear alpha-synuclein is present in the human brain and is modified in dementia with Lewy bodies Dementia with Lewy bodies is pathologically defined by the cytoplasmic accumulation of alpha-synuclein within neuronal cells in the brain. Alpha-synuclein is predominately pre-synaptic, but has been reported present in various subcellular compartments in cell and animal models. In particular, nuclear alpha-synuclein is evident in-vitro and in disease models and has been associated with altered DNA integrity, gene transcription, nuclear homeostasis. However, owing to various factors, the presence of alpha-synuclein in the nuclei of human brain cells remains controversial, as does its role in synucleinopathies.

Here, we close this gap and provide a unique demonstration confirming the presence of nuclear alpha-synuclein in post-mortem brain tissue obtained from cases of dementia with Lewy bodies as well as from controls via immunohistochemistry, immunoblot, and label-free mass-spectrometry.

Discrete intra-nuclear alpha-synuclein puncta reactive against phosphorylated serine 129-alpha-synuclein and pan-alpha-synuclein antibodies were observed in cortical neurons and non-neuronal cells in fixed brain sections and in isolated nuclear preparations from Dementia with Lewy bodies cases and matched controls. Subsequent biochemical analysis of subcellular fractionated tissue confirmed alpha-synuclein as present in a nuclear fraction at levels ~ 10-fold lower than in the cytoplasm. Critically, however, an increase in monomeric nuclear alpha-synuclein phosphorylated as serine 129 was observed in cases of dementia with Lewy bodies alongside higher molecular weight pan- and phosphorylation reactive alpha-synuclein species, consistent with the formation of intranuclear phosphorylated alpha-synuclein oligomers. Furthermore, the presence of nuclear alpha-synuclein was confirmed via label free mass spectrometry, as 6 unique alpha-synuclein derived peptide sequences were identified in nuclear fractions (71.4% sequence coverage).

Collectively, our data confirm the presence of nuclear alpha-synuclein in human brain tissue and describe nuclear pathology associated with dementia with Lewy bodies. These findings address a major controversy in the synucleinopathy field by confirming the presence of nuclear alpha-synuclein in autoptic human brain tissue and, for the first time, identify that alpha-synuclein is aggregated into novel and potentially pathological assemblies in the nucleus as part of the disease process associated with dementia with Lewy bodies and thus may contribute to the disease phenotype. Nucleic Transformer: Deep Learning on Nucleic Acids with Self-attention and Convolutions AO_SCPLOWBSTRACTC_SCPLOWMuch work has been done to apply machine learning and deep learning to genomics tasks, but these applications usually require extensive domain knowledge and the resulting models provide very limited interpretability. Here we present the Nucleic Transformer, a conceptually simple but effective and interpretable model architecture that excels in a variety of DNA/RNA tasks. The Nucleic Transformer processes nucleic acid sequences with self-attention and convolutions, two deep learning techniques that have proved dominant in the fields of computer vision and natural language processing. We demonstrate that the Nucleic Transformer can be trained in both supervised and unsupervised fashion without much domain knowledge to achieve high performance with limited amounts of data in Escherichia coli promoter classification, viral genome identification, and degradation properties of COVID-19 mRNA vaccine candidates. Additionally, we showcase extraction of promoter motifs from learned attention and how direct visualization of self-attention maps assists informed decision making using deep learning models. A non-canonical convergence of carbohydrate and glutamine metabolism is required after metabolic rewiring in a solid environment The fate of pyruvate, which is modulated by the activity of the mitochondrial pyruvate carrier (MPC), is a defining metabolic feature in many cancers. Diffuse large B-cell lymphomas (DLBCLs) are a genetically and metabolically heterogeneous cancer. Although MPC expression and activity differed between DLBCL subgroups, mitochondrial pyruvate was uniformly consumed by glutamate pyruvate transaminase 2 (GPT2) to support -ketoglutarate production as part of glutaminolysis. This led us to discover that glutamine exceeds pyruvate as a carbon source for the tricarboxylic acid (TCA) cycle in DLBCLs. Furthermore, we found that MPC inhibition unexpectedly leads to decreased glutaminolysis, which is contrary to previous observations in other cell types. We also discovered that MPC inhibition and depletion only decreased DLBCL proliferation in an extracellular matrix (ECM) environment and in vivo xenografts, but not in the typical DLBCL suspension environment. We also have found that the metabolic profile of DLBCL cells in ECM is markedly different from cells in suspension environment. Thus, we report that besides the canonical glutamate dehydrogenase (GDH)-mediated glutaminolysis, the non-canonical GPT2 mediated consumption and assimilation of glutamine and pyruvate in DLBCLs enables their proliferation in an extracellular environment-dependent manner.

HIGHLIGHTSO_LIGlutamine, but not glucose, is a major carbon source for the tricarboxylic acid cycle in diffuse large B-cell lymphomas.
C_LIO_LIMitochondrial pyruvate supports glutaminolysis in diffuse large B-cell lymphomas by supplying pyruvate for glutamate pyruvate transaminase 2-mediated  -ketoglutarate production.
C_LIO_LIMitochondrial pyruvate carrier inhibition leads to decreased glutaminolysis in diffuse large B-cell lymphomas.
C_LIO_LI -ketoglutarate production is important for diffuse large B-cell lymphoma proliferation in a solid extracellular matrix environment.
C_LIO_LIMitochondrial pyruvate carrier activity supports diffuse large B-cell lymphoma proliferation in a solid extracellular matrix environment and in mouse xenografts.
C_LI Assigning metabolic rate measurements to torpor and euthermy in heterothermic endotherms: 'torpor', a new package for R. Torpor is a state of controlled reduction of metabolic rate (M) in endotherms. Assigning measurements of M to torpor or euthermy can be challenging, especially when the difference between euthermic M and torpid M is small, in species defending a high minimal body temperature in torpor, in thermolabile species, and slightly below the thermoneutral zone (TNZ). Here, we propose a novel method for distinguishing torpor from euthermy. We use the variation in M measured during euthermic rest and torpor at varying ambient temperatures (Ta) to objectively estimate the lower critical temperature (Tlc) of the TNZ and to assign measurements to torpor, euthermic rest or rest within TNZ. In addition, this method allows the prediction of M during euthermic rest and torpor at varying Ta, including resting M within the TNZ. The present method has shown highly satisfactory results using 28 published sets of metabolic data obtained by respirometry on 26 species of mammals. Ultimately, this novel method aims to facilitate analysis of respirometry data in heterothermic endotherms. Finally, the development of the associated R-package (torpor) will enable widespread use of the method amongst biologists.

Summary statementThe presented method and its associated R-package (torpor) enable the assignment of metabolic rate measurements to torpor or euthermy, ultimately improving the standardization of respirometry analyses in heterotherms. Synchrony and idiosyncrasy in the gut microbiome of wild baboons Human gut microbial dynamics are highly individualized, making it challenging to link microbiota to health and to design universal microbiome therapies. This individuality is typically attributed to variation in host genetics, diets, environments, and medications, but it could also emerge from fundamental ecological forces that shape microbiota more generally. Here we leverage extensive gut microbial time series from wild baboons--hosts who experience little interindividual dietary and environmental heterogeneity--to test whether gut microbial dynamics are synchronized across hosts or largely idiosyncratic. Despite their shared lifestyles, baboon microbiome dynamics were only weakly synchronized. The strongest synchrony occurred among baboons living in the same social group, likely because group members range over the same habitat and simultaneously encounter the same sources of food and water. However, this synchrony was modest compared to each hosts personalized dynamics. Indeed, host-specific factors, especially host identity, explained 10 times the deviance in longitudinal microbial dynamics, compared to factors shared across hosts. These results contribute to mounting evidence that highly idiosyncratic gut microbiomes are not an artifact of modern human environments, and that synchronizing forces in the gut microbiome (e.g., shared environments, diets, and microbial dispersal) are often not strong enough to overwhelm drivers of microbiome personalization, including host genetics, priority effects, horizontal gene transfer, and functional redundancy. Intramolecular carbon isotope signals reflect metabolite allocation in plants Stable isotopes at natural abundance are key tools to study physiological processes occurring outside the temporal scope of manipulation and monitoring experiments. Whole-molecule carbon isotope ratios (13C/12C) enable assessments of plant carbon uptake yet conceal information about carbon allocation. Here, we identify an intramolecular 13C/12C signal at treering glucose C-5 and C-6 and develop experimentally testable theories on its origin. More specifically, we assess the potential of processes within C3 metabolism for signal introduction based (inter alia) on constraints on signal propagation posed by metabolic networks. We propose that the intramolecular signal reports carbon allocation into major metabolic pathways in actively photosynthesising leaf cells including the anaplerotic, shikimate, and non-mevalonate pathway. We support our theoretical framework by linking it to previously reported whole-molecule 13C/12C increases in cellulose of ozone-treated Betula pendula and a highly significant relationship between the intramolecular signal and tropospheric ozone concentration. Our theory postulates a pronounced preference of leaf-cytosolic triose-phosphate isomerase to catalyse the forward reaction in vivo (dihydroxyacetone phosphate to glyceraldehyde 3-phosphate). In conclusion, intramolecular 13C/12C analysis resolves information about carbon uptake and allocation enabling more comprehensive assessments of carbon metabolism than whole-molecule 13C/12C analysis.

HighlightIntramolecular 13C/12C analysis resolves information about carbon uptake and allocation (and associated environmental controls) enabling more comprehensive assessments of carbon metabolism, plant-environment interactions, and environmental variability than whole-molecule 13C/12C analysis. A novel nongenetic murine model of hyperglycemia and hyperlipidemia-associated aggravated atherosclerosis ObjectiveAtherosclerosis, the main pathology underlying cardiovascular diseases is accelerated in diabetic patients. Genetic mouse models require breeding efforts which are time-consuming and costly. Our aim was to establish a new nongenetic model of inducible metabolic risk factors that mimics hyperlipidemia, hyperglycemia, or both and allows the detection of phenotypic differences dependent on the metabolic stressor(s).

Methods and ResultsWild-type mice were injected with gain-of-function PCSK9D377Y (proprotein convertase subtilisin/kexin type 9) mutant adeno-associated viral particles (AAV) and streptozotocin and fed either a high-fat diet (HFD) for 12 or 20 weeks or a high-cholesterol/high-fat diet (Paigen diet, PD) for 8 weeks. To evaluate atherosclerosis, two different vascular sites (aortic sinus and the truncus of the brachiocephalic artery) were examined in the mice. Combined hyperlipidemic and hyperglycemic (HGHCi) mice fed a HFD or PD displayed characteristic features of aggravated atherosclerosis when compared to hyperlipidemia (HCi HFD or PD) mice alone. Atherosclerotic plaques of HGHCi HFD animals were larger, showed a less stable phenotype (measured by the increased necrotic core area, reduced fibrous cap thickness, and less -SMA-positive area) and had more inflammation (increased plasma IL-1{beta} level, aortic pro-inflammatory gene expression, and MOMA-2-positive cells in the BCA) after 20 weeks of HFD. Differences between the HGHCi and HCi HFD models were confirmed using RNA-seq analysis of aortic tissue, revealing that significantly more genes were dysregulated in mice with combined hyperlipidemia and hyperglycemia than in the hyperlipidemia-only group. The HGHCi-associated genes were related to pathways regulating inflammation (increased Cd68, iNos, and Tnfa expression) and extracellular matrix degradation (Adamts4 and Mmp14). When comparing HFD with PD, the PD aggravated atherosclerosis to a greater extent in mice and showed plaque formation after 8 weeks. Hyperlipidemic and hyperglycemic mice fed a PD (HGHCi PD) showed less collagen (Sirius red) and increased inflammation (CD68-positive cells) within aortic plaques than hyperlipidemic mice (HCi PD). HGHCi-PD mice represent a directly inducible hyperglycemic atherosclerosis model compared with HFD-fed mice, in which atherosclerosis is severe by 8 weeks.

ConclusionWe established a nongenetically inducible mouse model allowing comparative analyses of atherosclerosis in HCi and HGHCi conditions and its modification by diet, allowing analyses of multiple metabolic hits in mice. CIITA induces expression of MHC-I and MHC-II in transmissible cancers MHC-I and MHC-II molecules are critical components of antigen presentation and T cell immunity to pathogens and cancer. The two monoclonal transmissible devil facial tumours (DFT1, DFT2) exploit MHC-I pathways to overcome immunological anti-tumour and allogeneic barriers. This exploitation underpins the ongoing transmission of DFT cells across the wild Tasmanian devil population. We have previously shown that constitutive expression of NLRC5 can induce stable upregulation of MHC-I on DFT1 and DFT2 cells, but unlike IFNG-treated cells, NLRC5 does not upregulate PDL1. MHC-II expression is crucial for CD4+ T cell activation and is primarily confined to haematopoietic antigen presenting cells. Transcriptomic analysis of DFT1 and DFT2 cell lines showed that several genes of the MHC-I and MHC-II pathways were upregulated in response to constitutive overexpression of the class II transactivator (CIITA) gene. This was further supported by upregulation of MHC-I protein on DFT1 and DFT2 cells, but interestingly MHC-II protein was upregulated only on DFT1 cells. The functional significance of the MHC upregulation on DFT cells was shown using serum from devils with natural or immunotherapy-induced DFT1 regressions; binding of serum IgG was stronger in CIITA-transfected cells than wild type cells, but was less than binding to NLRC5 transfected cells. This new insight into regulation of MHC-I and MHC-II in cells that naturally overcome allogeneic barriers can inform vaccine, immunotherapy, and tissue transplant strategies for human and veterinary medicine. Simple and practical sialoglycan encoding system reveals vast diversity in nature and identifies a universal sialoglycan-recognizing probe derived from AB5 toxin B subunits Vertebrate sialic acids (Sias) display much diversity in modifications, linkages and underlying glycans. Slide microarrays allow high-throughput explorations of sialoglycan-protein interactions. A microarray presenting [~]150 structurally-defined sialyltrisaccharides with various Sias linkages and modifications still poses challenges in planning, data sorting, visualization and analysis. To address these issues, we devised a simple 9-digit code for sialyltrisaccharides with terminal Sias and underlying two monosaccharides assigned from the non-reducing end, with three digits assigning a monosaccharide, its modifications, and linkage. Calculations based on the encoding system reveals >113,000 likely linear sialyltrisaccharides in nature. Notably a biantennary N-glycan with two terminal sialyltrisaccharides could thus have >1010 potential combinations and a triantennary N-glycan with three terminal sequences, >1015 potential combinations. While all possibilities likely do not exist in nature, sialoglycans encode enormous diversity. While glycomic approaches are used to probe such diverse sialomes, naturally-occurring bacterial AB5 toxin B subunits are simpler tools to track the dynamic sialome in biological systems. Sialoglycan microarray was utilized to compare sialoglycan-recognizing bacterial toxin B subunits. Unlike the poor correlation between B subunits and species phylogeny, there is stronger correlation with Sia-epitope preferences. Further supporting this pattern, we report a B subunit (YenB) from Yersinia enterocolitica (broad host range) recognizing almost all sialoglycans in the microarray, including 4-O-acetylated-Sias not recognized by a Y. pestis orthologue (YpeB). Differential Sia-binding patterns were also observed with phylogenetically-related B subunits from Escherichia coli (SubB), Salmonella Typhi (PltB), S. Typhimurium (ArtB), extra-intestinal E.coli (EcPltB), Vibrio cholera (CtxB), and cholera family homologue of E. coli (EcxB). Purkinje Cell Activity in Medial and Lateral Cerebellum During Suppression of Voluntary Eye Movements in Rhesus Macaques Volitional suppression of responses to distracting external stimuli enables us to achieve our goals. This volitional inhibition of a specific behavior is supposed to be mainly mediated by the cerebral cortex. However, recent evidence supports the involvement of the cerebellum in this process. It is currently not known whether different parts of the cerebellar cortex play differential or synergistic roles in planning and execution of this behavior. Here, we measured Purkinje cell (PC) responses in the medial and lateral cerebellum in two rhesus macaques during a pro- and antisaccade task. During an antisaccade trial, non-human primates were instructed to make a saccadic eye movement away from a target, rather than towards it, as in prosaccade trials. Our data shows that the cerebellum plays an important role not only during execution of the saccades, but also during the volitional inhibition of eye movements towards the target. Simple Spike (SS) modulation during the instruction and execution period of pro- and antisaccades was prominent in PCs of both medial and lateral cerebellum. However, only the SS activity in the lateral cerebellar cortex contained information about trial identity and showed a stronger reciprocal interaction with complex spikes. Moreover, SS activity of different PC groups modulated bidirectionally in both regions, but the PCs that showed facilitating and suppressive activity were predominantly associated with instruction and execution, respectively. These findings show that different cerebellar regions and PC groups contribute to goal-directed behavior and volitional inhibition, but with different propensities, highlighting the rich repertoire of cerebellar control in executive functions.

Significance StatementThe antisaccade task is commonly used in research and clinical evaluation as a test of volitional and flexible control of behavior. It requires volitional suppression of prosaccades, a function that has been attributed to the neocortex. However, recent findings indicate that cerebellum also contributes to this behavior. We recorded from neurons in the medial and lateral cerebellum to evaluate their responses in this task. We found that both regions significantly modulated their activity during this task, but only cells in the lateral cerebellum encoded the stimulus identity in each trial. These results indicate that the cerebellum actively contributes to the control of flexible behavior and that lateral and medial cerebellum play different roles during volitional eye movements. Affordable Caenorhabditis elegans tracking system for classroom use For decades the nematode C. elegans has served as an outstanding research organism owing to its unsurpassed experimental amenability. This advantage has also made this tiny worm an attractive vehicle for science instruction across higher learning institutions. However, the prohibitive cost associated with the automated behavioral assessment of these animals remains an obstacle preventing their full adoption in undergraduate and high school settings. To improve this situation, we developed an inexpensive worm tracking system for use by high school interns and undergraduate students. Over the past two years this tracker has been successfully used by undergraduate students in our introductory Cell and Molecular lab (BSC220) at Illinois State University. Here we describe and demonstrate the use of our inexpensive worm tracking system. A generic hidden Markov model for multi-parent populations A common step in the analysis of multi-parent populations is genotype reconstruction: identifying the founder origin of haplotypes from dense marker data. This process often makes use of a probability model for the pattern of founder alleles along chromosomes, including the relative frequency of founder alleles and the probability of exchanges among them, which depend on a model for meiotic recombination and on the mating design for the population. While the precise experimental design used to generate the population may be used to derive a precise characterization of the model for exchanges among founder alleles, this can be tedious, particularly given the great variety of experimental designs that have been proposed. We describe an approximate model that can be applied for a variety of multi-parent populations. We have implemented the approach in the R/qtl2 software, and we illustrate its use in applications to publicly-available data on Diversity Outbred and Collaborative Cross mice A pilot study on the home range and movement patterns of the Andean Fox Lycalopex culpaeus (Molina 1782) in Cotopaxi National Park, Ecuador This study reports movement patterns and home range estimates of an Andean fox (Lycalopex culpaeus) in Cotopaxi National Park in Ecuador, representing the first GPS-tagging of the species. The GPS functioned well during the 197-day tracking period. Home range sizes ranged between 4.9 - 8.1 km2, depending on the estimation method. Movement speeds averaged 0.17 km/hr at day vs. 0.87 km/hr. at night, and distance traveled averaged 0.23 km at day vs. 0.89 km at night. These preliminary results highlight the importance of collecting unbiased, high-quality data which enables an enhanced understanding on mammal behavior and human/animal interaction. Assessing the Role of Calmodulin's Linker Flexibility in Target Binding 1Calmodulin (CaM) is a universal Ca2+ binding protein known to bind at least 300 targets. The selectivity and specificity towards these targets are partially attributed to the proteins flexible alpha-helical linker that connects its N- and C-domains. How this flexible linker mediates the driving forces guiding CaMs binding to regulatory targets is not well-established. Therefore, we utilized the Martini coarse-grained (CG) molecular dynamics simulations to probe interrelationships between CaM/target assembly and the role of its linker region. As a model system, we simulated the binding of CaM to the CaM binding region (CaMBR) of calcineurin (CaN). The simulations were conducted assuming a  wild-type calmodulin with normal flexibility of its linker, as well as a labile, highly flexible linker variant. For the wild-type model, 98% of the 600 simulations across three ionic strengths adopted a bound complex within 2 {micro}s of simulation time; of these, 1.7% sampled the fully-bound state observed in experimentally-determined crystallographic structure. By calculating the mean-first-passage-time for these simulations, we estimated the association rate to be ka = 5.9 x 108 M-1 s-1, which is similar to the experimentally-determined rate of 2.2 x 108 M-1 s-1 [1]. Further, our simulations recapitulated the inverse relationship between the association rate and solution ionic strength reported in the literature. In contrast, although over 97% of the labile linker simulations formed tightly-bound complexes, only 0.3% achieved the fully-bound configuration. This effect appears to stem from a difference in the ensembles of extended and collapsed states controlled by the linker properties. Specifically, the labile linker variant samples fewer extended states compatible with target peptide binding. Therefore, our simulations suggest that variations in the CaM linkers propensity for alpha-helical secondary structure can modulate the kinetics of target binding. This finding is important, as the linker region houses several CaM variants sites for post-translational modifications, that may alter the proteins normal regulatory functions. The cortical bone metabolome of C57BL/6J mice is sexually dimorphic Cortical bone quality, which is sexually dimorphic, depends on bone turnover and therefore the activities of remodeling bone cells. However, sex differences in cortical bone metabolism are not yet defined. Adding to the uncertainty about cortical bone metabolism, the metabolomes of whole bone, isolated cortical bone without marrow, and bone marrow have not been compared. We hypothesized that the metabolome of isolated cortical bone would be distinct from that of bone marrow and would reveal sex differences. Metabolite profiles from LC-MS of whole bone, isolated cortical bone, and bone marrow were generated from humeri from 20-week-old female C57Bl/6J mice. The cortical bone metabolomes were then compared for 20-week-old female and male C57Bl/6J mice. Femurs from male and female mice were evaluated for flexural material properties and were then categorized into bone strength groups. The metabolome of isolated cortical bone was distinct from both whole bone and bone marrow. We also found sex differences in the isolated cortical bone metabolome. Based on metabolite pathway analysis, females had higher lipid metabolism, and males had higher amino acid metabolism. High-strength bones, regardless of sex, had greater tryptophan and purine metabolism. For males, high strength bones had upregulated nucleotide metabolism, whereas lower strength bones had greater pentose phosphate pathway metabolism. Since the higher strength groups (females compared with males, high strength males compared with lower strength males) had higher serum CTX1/P1NP, we estimate that the metabolomic signature of bone strength in our study at least partially reflects differences in bone turnover. These data provide novel insight into bone bioenergetics and the sexual dimorphic nature of bone material properties in C57Bl/6 mice. Ecological interactions in breast cancer: Cell facilitation promotes growth and survival under drug pressure The interplay of positive and negative interactions between drug sensitive and resistant cells determines the efficacy of treatment in heterogeneous cancer cell populations. We developed isogenic estrogen receptor positive (ER+) breast cancer cell lineages sensitive and resistant to ribociclib-induced CDK4/6 inhibition to investigate cell interactions under selective pressure. During treatment with ribociclib alone or in combination with endocrine therapies, sensitive cells survive and proliferate better when grown together with resistant cells than when grown in monoculture. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) assays detected estrone, a less active metabolite, in medium taken from each lineage but detected highly active estradiol only from resistant cells. Because sensitive cells are more dependent on estrogen signaling than resistant cells, they benefit from the increase in local estradiol from resistant cells, leading to facilitated growth when grown under treatment in coculture. We developed a suite of mathematical models to quantify the strength of competition and facilitation between cell lines and evaluate the effects of treatments that modify these interactions. These analyses support the conclusion that resistant cell lineages facilitate growth of sensitive lineages during therapy through the increased production and sharing of local estradiol and themselves suffer from increased competition and suppression as a result. These models show that blocking facilitation has the potential to control both resistant and sensitive cell populations and inhibit the emergence of a refractory population. This combination of experiments and models shows that interactions within heterogeneous cancer cell populations can combine positive and negative interactions to shape the dynamics of resistance. FACT regulates pluripotency through distal regulation of gene expression in murine embryonic stem cells The FACT complex is a conserved histone chaperone with essential roles in transcription and histone deposition. FACT is essential in pluripotent and cancer cells, but otherwise dispensable for most mammalian cell types. FACT deletion or inhibition can block induction of pluripotent stem cells, yet the mechanism through which FACT regulates cell fate decisions remains unclear. To determine this mechanism, we used inducible depletion of FACT subunit SPT16 in murine embryonic stem cells paired with genomic factor localization, nascent transcription, and chromatin accessibility analyses. Over a timecourse of SPT16 depletion, nucleosomes invade loci bound by master pluripotency factors and gene-distal DNaseI hypersensitive sites. Simultaneously, transcription of Pou5f1 (OCT4), Sox2, Nanog, and enhancer RNAs produced at the genes' associated enhancers are downregulated, suggesting that FACT regulates expression of the pluripotency factors themselves. We find that FACT maintains cellular pluripotency through a precise nucleosome-based regulatory mechanism for appropriate expression of both coding and non-coding transcripts associated with pluripotency.