Miracle-dz/UniFAR-FTUs huggingface dataset:
Resolving the step size in condensin-driven DNA loop extrusion identifies ATP binding as the step-generating process

The condensin SMC protein complex organizes chromosomal structure by extruding loops of DNA. Its ATP-dependent motor mechanism remains unclear but likely involves steps associated with large conformational changes within the ~50 nm protein complex. Here, using magnetic tweezers, we resolve single steps in loop extrusion by individual yeast condensins. Step sizes range between 20-45 nm at forces of 1.0-0.2 pN, respectively, comparable to the complex size. The large steps show that condensin reels in DNA in very sizeable amounts, up to ~600 bp per extrusion step, consistent with the non-stretched DNA polymer at these low forces. Using ATP-binding-impaired and ATP-hydrolysis-deficient mutants, we find that ATP binding is the primary step-generating stage underlying DNA loop extrusion. We discuss the findings in terms of a scrunching model where a stepwise DNA loop extrusion is generated by an ATP-binding-induced engagement of the hinge and the globular domain of the SMC complex.
Implementing the precautionary approach into fisheries management: Making the case for probability-based harvest control rules

The precautionary approach to fisheries management advocates for risk-averse management strategies that include biological reference points as well as decision rules and account for scientific uncertainty. In this regard, two approaches have been recommended: (i) harvest control rules (HCRs) with threshold reference points to safeguard against low stock biomass, and (ii) the P* method, a ‘probability-based HCR’ that reduces the catch limit as a function of scientific uncertainty (i.e. process, model, and observation uncertainty). This study compares the effectiveness of these precautionary approaches in recovering over-exploited fish stocks with various life-history traits and under a wide range of levels of scientific uncertainty. We use management strategy evaluation based on a stochastic, age-based operating model with quarterly time steps and a stochastic surplus production model. The results show that the most effective HCR includes both a biomass threshold as well as the P* method, and leads to high and stable long-term yield with a decreased risk of low stock biomass. For highly dynamics stocks, management strategies that aim for higher biomass targets than the traditionally used BMSY result in higher long-term yield. This study makes the case for probability-based HCRs by demonstrating their benefit over deterministic HCRs and provides a list of recommendations regarding their definition and implementation.
Performance of deep learning restoration methods for the extraction of particle dynamics in noisy microscopy image sequences

Image-based particle tracking is an essential tool to answer research questions in cell biology and beyond. A major challenge of particle tracking in living systems is that low light exposure is required to avoid phototoxicity and photobleaching. In addition, high-speed imaging used to fully capture particle motion dictates fast image acquisition rates. Short exposure times come at the expense of tracking accuracy. This is generally true for quantitative microscopy approaches and particularly relevant to single molecule tracking where the number of photons emitted from a single chromophore is limited. Image restoration methods based on deep learning dramatically improve the signal-to-noise ratio in low-exposure datasets. However, it is not clear whether images generated by these methods yield accurate quantitative measurements such as diffusion parameters in (single) particle tracking experiments. Here, we evaluate the performance of two popular deep learning denoising software packages for particle tracking, using synthetic datasets and movies of diffusing chromatin as biological examples. With synthetic data, both supervised and unsupervised deep learning restored particle motions with high accuracy in two-dimensional datasets, whereas artifacts were introduced by the denoisers in 3D datasets. Experimentally, we found that, while both supervised and unsupervised approaches improved the number of trackable particles and tracking accuracy, supervised learning generally outperformed the unsupervised approach, as expected. We also highlight that with extremely noisy image sequences, deep learning algorithms produce deceiving artifacts, which underscores the need to carefully evaluate the results. Finally, we address the challenge of selecting hyper-parameters to train convolutional neural networks by implementing a frugal Bayesian optimizer that rapidly explores multidimensional parameter spaces, identifying networks yielding optional particle tracking accuracy. Our study provides quantitative outcome measures of image restoration using deep learning. We anticipate broad application of the approaches presented here to critically evaluate artificial intelligence solutions for quantitative microscopy.
The SARS-CoV-2 and other human coronavirus spike proteins are fine-tuned towards temperature and proteases of the human airways

The high transmissibility of SARS-CoV-2 is related to abundant replication in the upper airways, which is not observed for the other highly pathogenic coronaviruses SARS-CoV-1 and MERS-CoV. We here reveal features of the coronavirus spike (S) protein, which optimize the virus towards different parts of the respiratory tract. First, the SARS-CoV-2 spike (SARS-2-S) reached higher levels in pseudoparticles when produced at 33°C instead of 37°C. Even stronger preference for the upper airway temperature of 33°C was evident for the S protein of HCoV-229E, a common cold coronavirus. In contrast, the S proteins of SARS-CoV-1 and MERS-CoV favored 37°C, in accordance with their preference for the lower airways. Next, SARS-2-S proved efficiently activated by TMPRSS13, besides the previously identified host cell protease TMPRSS2, which may broaden the cell tropism of SARS-CoV-2. TMPRSS13 was found to be an effective spike activator for the virulent coronaviruses but not the common cold HCoV-229E virus. Activation by these proteases requires pre-cleavage of the SARS-2-S S1/S2 cleavage loop, and both its furin motif and extended loop length proved critical to achieve virus entry into airway epithelial cells. Finally, we show that the D614G mutation in SARS-2-S increases S protein stability and expression at 37°C, and promotes virus entry via cathepsin B/L activation. These spike properties might promote virus spread, potentially explaining why the G614 variant is currently predominating worldwide. Collectively, our findings indicate how the coronavirus spike protein is fine-tuned towards the temperature and protease conditions of the airways, to enhance virus transmission and pathology. SIGNIFICANCE STATEMENT The rapid spread of SARS-CoV-2, the cause of COVID-19, is related to abundant replication in the upper airways, which is not observed for other highly pathogenic human coronaviruses. We here reveal features of the coronavirus spike (S) protein, which optimize the virus towards different parts of the respiratory tract. Coronavirus spikes exhibit distinct temperature preference to precisely match the upper (~33°C) or lower (37°C) airways. We identified airway proteases that activate the spike for virus entry into cells, including one protease that may mediate coronavirus virulence. Also, a link was seen between spike stability and entry via endosomal proteases. This mechanism of spike fine-tuning could explain why the SARS-CoV-2 spike-D614G mutant is more transmissible and therefore globally predominant.
Temporal patterning of the central nervous system by a shared transcription factor code

The molecular mechanisms that ensure the reproducible generation of neuronal diversity in the vertebrate nervous system are incompletely understood. Here we provide evidence of a temporal patterning program consisting of cohorts of transcription factors expressed in neurons generated at successive developmental timepoints. This program acts in parallel to spatial patterning, diversifying neurons throughout the nervous system and in neurons differentiated in-vitro from stem cells. We demonstrate the TGFβ signalling pathway controls the pace of the temporal program. Furthermore, targeted perturbation of components of the temporal program, Nfia and Nfib, reveals their requirement for the generation of late-born neuronal subtypes. Together, our results provide evidence for the existence of a previously unappreciated global temporal program of neuronal subtype identity and suggest that the integration of spatial and temporal patterning programs diversifies and organises neuronal subtypes in the vertebrate nervous system.
Insula cortex gates the interplay of action observation and preparation for controlled imitation

Perceiving, anticipating and responding to the actions of another person are fundamentally entwined processes such that seeing another’s movement can prompt automatic imitation, as in social mimicry and contagious yawning. Yet the direct-matching of others’ movements is not always appropriate, so this tendency must be controlled. This necessitates the hierarchical integration of the systems for action mirroring with domain-general control networks. Here we use functional magnetic resonance imaging (fMRI) and computational modelling to examine the top-down and context-dependent modulation of mirror representations and their influence on motor planning. Participants performed actions that either intentionally or incidentally imitated, or counter-imitated, an observed action. Analyses of these fMRI data revealed a region in the mid-occipital gyrus (MOG) where activity differed between imitation versus counter-imitation in a manner that depended on whether this was intentional or incidental. To identify broader cortical network mechanisms underlying this interaction between intention and imitativeness, we used dynamic causal modelling to pose specific hypotheses which embody assumptions about inter-areal interactions and contextual modulations. These models each incorporated four regions - medial temporal V5 (early motion perception), MOG (action-observation), supplementary motor area (action planning), and anterior insula (executive control) – but differ in their interactions and hierarchical structure. The best model of our data afforded a crucial role for the anterior insula, gating the interaction of supplementary motor area and MOG activity. This provides a novel brain network-based account of task-dependent control over the integration of motor planning and mirror systems, with mirror responses suppressed for intentional counter-imitation.
Linguistic processing of task-irrelevant speech at a Cocktail Party

Paying attention to one speaker in noisy environments can be extremely difficult. This is because task-irrelevant speech competes for processing resources with attended speech. However, whether this competition is restricted to acoustic-phonetic interference, or if it extends to competition for linguistic processing as well, remains highly debated. To address this debate, here we test whether task-irrelevant speech sounds are integrated over time to form hierarchical representations of lexical and syntactic structures. Neural activity was recorded using Magnetoencephalography (MEG) during a dichotic listening task, where human participants attended to natural speech presented to one ear, and task-irrelevant stimuli were presented to the other. Task-irrelevant stimuli consisted either of random sequences of syllables (Non-Structured), or syllables ordered to form coherent sentences (Structured). Using hierarchical frequency-tagging, the neural signature of different linguistic-hierarchies within the Structured stimuli – namely words, phrases and sentences – can be uniquely discerned from the neural response. We find that, indeed, the phrasal structure of task-irrelevant stimuli was represented in the neural response, primarily in left inferior frontal and posterior parietal regions. Moreover, neural tracking of attended speech in left inferior frontal regions was enhanced when task-irrelevant stimuli were linguistically structured. This pattern suggests that syntactic structurebuilding processes are applied to task-irrelevant speech, at least under these circumstances, and that selective attention does not fully eliminate linguistic processing of task-irrelevant speech. Rather, the inherent competition for linguistic processing resources between the two streams likely results in the increased listening effort experienced when trying to focus selective attention in multi-speaker contexts. Significance statement This study addresses the fundamental question of how the brain deals with competing speech in noisy environments. Specifically, we ask: when one attempts to focus their attention on a particular speaker, what level of linguistic processing is applied to other, task-irrelevant speech? By measuring neural activity, we find evidence that the phrasal structure of task-irrelevant speech is indeed discerned, indicating that linguistic information is integrated over time and undergoes some syntactic analysis. Moreover, neural responses to attended speech were also enhanced in speech-processing regions, when presented together with comprehensible yet task-irrelevant speech. These results nicely demonstrate the inherent competition for linguistic processing resources among concurrent speech, providing evidence that selective attention does not fully eliminate linguistic processing of task-irrelevant speech.
What Markov state models can and cannot do: Correlation versus path-based observables in protein folding models

Markov state models (MSMs) have been widely applied to study the kinetics and pathways of protein conformational dynamics based on statistical analysis of molecular dynamics (MD) simulations. These MSMs coarse-grain both configuration space and time in ways that limit what kinds of observables they can reproduce with high fidelity over different spatial and temporal resolutions. Despite their popularity, there is still limited understanding of which biophysical observables can be computed from these MSMs in a robust and unbiased manner, and which suffer from the space-time coarse-graining intrinsic in the MSM model. Most theoretical arguments and practical validity tests for MSMs rely on long-time equilibrium kinetics, such as the slowest relaxation timescales and experimentally observable time-correlation functions. Here, we perform an extensive assessment of the ability of well-validated protein folding MSMs to accuractely reproduce path-based observable such as mean first-passage times (MFPTs) and transition path mechanisms compared to a direct trajectory analysis. We also assess a recently proposed class of history-augmented MSMs (haMSMs) that exploit additional information not accounted for in standard MSMs. We conclude with some practical guidance on the use of MSMs to study various problems in conformational dynamics of biomolecules. In brief, MSMs can accurately reproduce correlation functions slower than the lag time, but path-based observables can only be reliably reproduced if the lifetimes of states exceed the lag time, which is a much stricter requirement. Even in the presence of short-lived states, we find that haMSMs reproduce path-based observables more reliably.
TRPM2 promotes pancreatic cancer by PKC/MAPK pathway

The mechanism of pancreatic cancer (PA) is not fully understanded. In our last report, TRPM2 plays a promising role in pancreatic cancer. However, the mechanism of TRPM2 is still unknown in this dismal disease. This study was designed to investigate the role and mechanism of TRPM2 in pancreatic cancer. TRPM2 overexpressed and siRNA plasmid were created and transfected with pancreatic cancer cell line (BxPC-3) to construct the cell model. We employed CCK-8, Transwell, scratch wound, and nude mice tumor-bearing model to investigate the role of TRPM2 in pancreatic cancer. Besides, we collected the clinical data, tumor tissue sample (TT) and para-tumor sample (TP) from the pancreatic cancer patients treated in our hospital. We analyzed the mechanism of TRPM2 in pancreatic cancer by transcriptome analysis, western blot, and PCR. We blocked the downstream PKC/MEK pathway of TRPM2 to investigate the mechanism of TRPM2 in pancreatic cancer by CCK8, scratch wound healing, and transwell assays. Overexpressed TRPM2 could promote pancreatic cancer in proliferation, migration, and invasion ability in no matter the cell model or nude mice tumor-bearing model. TRPM2 level is highly negative correlated to the overall survival and progression-free survival time in PA patients, however, it is significantly increased in PA tissue as the tumor stage increases. The transcriptome analysis, GSEA analysis, western-blot, and PCR results indicate TRPM2 is highly correlated with PKC/MAPK pathways. The experiments of PKC/MEK inhibitors added to TRPM2 overexpressed BxPC-3 cell showed that significant inhibition of PA cells happened in CCK8, transwell, and wound-healing assay. TRPM2 may directly activate PKCα by calcium or indirectly activate PKCε and PKCδ by increased DAG in PA, which promote PA by downstream MAPK/MEK pathway activation.
AMPK Modulates Associative Learning via Neuronal Mitochondrial Fusion in C. elegans

Loss of metabolic homeostasis is one of the hallmarks of the aging process that might contribute to pathogenesis by creating a permissive landscape over which neurodegenerative diseases can take hold. AMPK, a conserved energy sensor, extends lifespan and is protective in some neurodegenerative models. AMPK regulates mitochondrial homeostasis and morphology, however, whether mitochondrial regulation causally links AMPK to protection against loss of neuronal function with aging and diseases remains unclear. Here we use an associative learning protocol in C. elegans as a readout of neuronal function and show that AMPK activation enhances associative learning and prevents age-related loss of learning capacity. AMPK promotes neuronal mitochondrial fusion and mitochondrial fragmentation via fzo-1 deletion blocks AMPK’s effects on associative learning. Restoring mitochondrial fusion capacity specifically in the neurons rescued learning capacity downstream of AMPK. Finally, AMPK activation rescues neuronal Aβ1-42 induced loss of associative learning. Overall, our results suggest that targeting neuronal metabolic flexibility may be a viable therapeutic option to restore neuronal function in the context of aging and neurodegenerative diseases.
Reproduction of a marine planktonic protist: Individual success versus population survival

Understanding the biology of reproduction is important for retracing key evolutionary processes in organisms, yet gaining detailed insights often poses major challenges. Planktonic Foraminifera are globally distributed marine microbial eukaryotes and important contributors to the global carbon cycle. Their extant biodiversity shows restricted distribution patterns of some species, whereas others are cosmopolitan in the world ocean. Planktonic Foraminifera cannot be bred under laboratory conditions, and thus details of their life cycle remain incomplete. Solely the production of flagellated gametes has been observed and taken as an indication for an exclusively sexual reproduction. Yet, sexual reproduction by spawning of gametes in the open ocean relies on sufficient gamete encounters to maintain viable populations, which represents a problem for organisms that lack the means of active propulsion and are marked by low population densities. To increase knowledge on the reproductive biology of planktonic Foraminifera, we applied a dynamic, individual-based modelling approach with parameters based on laboratory and field observations to test if random gamete encounters under commonly observed population densities are sufficient for maintaining viable populations. We show that temporal synchronization and potentially spatial concentration of gamete release seems inevitable for maintenance of the population. We argue that planktonic Foraminifera optimized their individual reproductive success at the expense of community-wide gene flow, which may explain their high degree of diversity. Our modelling approach helps to illuminate foraminiferal population dynamics and to predict the existence of necessary reproduction strategies, which may be detected in future field experiments. This study therefore contributes to our understanding of plankton ecology and evolution and their reproductive strategies in the open ocean.
Pushing Raman spectroscopy over the edge: purported signatures of organic molecules in fossils are instrumental artefacts

Claims for the widespread preservation of fossilized biomolecules in many fossil animals have recently been reported in six studies, based on Raman microspectroscopy. Here, we show that the putative Raman signatures of organic compounds in these fossils are actually instrumental artefacts resulting from intense background luminescence. Raman spectroscopy relies upon the detection of photons scattered inelastically by matter as a result of its interaction with a laser beam. For many natural materials, this interaction also generates a luminescence signal that is often orders of magnitude more intense than the light produced by Raman scattering. Such luminescence, coupled with the transmission properties of the spectrometer, induced quasi-periodic ripples in the measured spectra that have been incorrectly interpreted as Raman signatures of organic molecules. Although several analytical strategies have been developed to overcome this common issue, Raman microspectroscopy as used in the studies questioned here cannot be used to identify fossil biomolecules.
Working memory gates visual input to primate prefrontal neurons

Visually guided behavior relies on the integration of sensory input with information held in working memory. Yet it remains unclear how this is accomplished at the level of neural circuits. We studied the direct visual cortical inputs to neurons within a visuomotor area of prefrontal cortex in behaving monkeys. We show that the synaptic efficacy of visual cortical input to prefrontal cortex is gated by information held in working memory. Surprisingly, visual input to prefrontal neurons was found to target those with both visual and motor properties, rather than preferentially targeting other visual neurons. Furthermore, activity evoked from visual cortex was larger in magnitude, more synchronous, and more rapid, when monkeys remembered locations that matched the location of visual input. These results indicate that working memory directly influences the circuitry that transforms visual input into visually guided behavior.
Retinal and cortical visual acuity in a common inbred albino mouse

While albino mice are widely used in research which includes the use of visually guided behavioral tests, information on their visual capability is scarce. We compared the spatial resolution (acuity) of albino mice (BALB/c) with that of pigmented mice (C57BL/6J). We used a high-throughput pattern electroretinogram (PERG) and pattern visual evoked potential (PVEP) method for objective assessment of retinal and cortical acuity, as well as optomotor head-tracking response/ reflex (OMR). We found that PERG, PVEP, and OMR acuities of C57BL/6J mice were all in the range of 0.5-0.6 cycles/degree (cyc/deg). BALB/c mice had PERG and PVEP acuities in the range of 0.1-0.2 cyc/deg but were unresponsive to OMR stimulus. Results indicate that retinal and cortical acuity can be reliably determined with electrophysiological methods in BALB/c mice, although PERG/PVEP acuities are lower than those of C57BL/6J mice. The reduced acuity of BALB/c mice appears to be primarily determined at retinal level.