Cell division protein FtsK coordinates bacterial chromosome segregation and daughter cell separation in Staphylococcus aureus.

Unregulated cell cycle progression may have lethal consequences and therefore, bacteria have various mechanisms in place for the precise spatiotemporal control of cell cycle events. We have uncovered a new link between chromosome replication/segregation and splitting of the division septum. We show that the DNA translocase domain-containing divisome protein FtsK regulates cellular levels of a peptidoglycan hydrolase Sle1, which is involved in cell separation in the bacterial pathogen Staphylococcus aureus. FtsK interacts with a chaperone (trigger factor, TF) and establishes a FtsK-dependent TF concentration gradient that is higher in the septal region. Trigger factor binds Sle1 and promotes its preferential export at the septal region, while also preventing Sle1 degradation by the ClpXP proteolytic machinery. Upon conditions that lead to paused septum synthesis, such as DNA damage or impaired DNA replication/segregation, TF gradient is dissipated and Sle1 levels are reduced, thus halting premature septum splitting.

A Near InfraRed Emissive Chemosensor for Zn2+ and Phosphate Derivatives Based on a Di-(2-picolyl)amine-styrylflavylium Push-Pull Fluorophore.

A new Near InfraRed (NIR) fluorescent chemosensor for metal ions and anions is herein presented. The fluorophore is based on a styrylflavylium dye, a synthetic analogue of the natural anthocyanin family, with a di-(2-picolyl)amine (DPA) moiety as the metal chelating unit. The substitution pattern of the styrylflavylium core (with tertiary amines on positions 7 and 4') shifts the optical properties of the dye towards the NIR region of the electronic spectra, due to a strong push-pull character over the π-conjugated system. The NIR chemosensor is highly sensitive to the presence of Zn2+, which induces a strong CHelation Enhanced Fluorescence (CHEF) effect upon binding to the DPA unit (2.7 fold increase). The strongest competing ion is Cu2+, with a complete fluorescence quenching, while other metals induce lower responses on the optical properties of the chemosensor. Subsequent anion screening of the Zn2+-chemosensor coordination compound has demonstrated a distinct selectivity towards adenosine 5'-triphosphate (ATP) and adenosine 5'-diphosphate (ADP), with high association constants (K ~ 106 M-1) and a strong CHEF effect (2.4 and 2.9 fold fluorescence increase for ATP and ADP, respectively). Intracellular studies with the Zn2+-complexed sensor showed strong luminescence in the cellular membrane of Gram- bacteria (E. coli) and mitochondrial membrane of mammalian cells (A659), which highlights its possible application for intracellular labelling.

Identification of 5-(Aryl/Heteroaryl)amino-4-quinolones as Potent Membrane-Disrupting Agents to Combat Antibiotic-Resistant Gram-Positive Bacteria.

Nosocomial infections caused by resistant Gram-positive organisms are on the rise, presumably due to a combination of factors including prolonged hospital exposure, increased use of invasive procedures, and pervasive antibiotic therapy. Although antibiotic stewardship and infection control measures are helpful, newer agents against multidrug-resistant (MDR) Gram-positive bacteria are urgently needed. Here, we describe our efforts that led to the identification of 5-amino-4-quinolone 111 with exceptionally potent Gram-positive activity with minimum inhibitory concentrations (MICs) ≤0.06 µg/mL against numerous clinical isolates. Preliminary mechanism of action and resistance studies demonstrate that the 5-amino-4-quinolones are bacteriostatic, do not select for resistance, and selectively disrupt bacterial membranes. While the precise molecular mechanism has not been elucidated, the lead compound is nontoxic displaying a therapeutic index greater than 500, is devoid of hemolytic activity, and has attractive physicochemical properties (clog P = 3.8, molecular weight (MW) = 441) that warrant further investigation of this promising antibacterial scaffold for the treatment of Gram-positive infections.

DeepBacs for multi-task bacterial image analysis using open-source deep learning approaches.

This work demonstrates and guides how to use a range of state-of-the-art artificial neural-networks to analyse bacterial microscopy images using the recently developed ZeroCostDL4Mic platform. We generated a database of image datasets used to train networks for various image analysis tasks and present strategies for data acquisition and curation, as well as model training. We showcase different deep learning (DL) approaches for segmenting bright field and fluorescence images of different bacterial species, use object detection to classify different growth stages in time-lapse imaging data, and carry out DL-assisted phenotypic profiling of antibiotic-treated cells. To also demonstrate the ability of DL to enhance low-phototoxicity live-cell microscopy, we showcase how image denoising can allow researchers to attain high-fidelity data in faster and longer imaging. Finally, artificial labelling of cell membranes and predictions of super-resolution images allow for accurate mapping of cell shape and intracellular targets. Our purposefully-built database of training and testing data aids in novice users' training, enabling them to quickly explore how to analyse their data through DL. We hope this lays a fertile ground for the efficient application of DL in microbiology and fosters the creation of tools for bacterial cell biology and antibiotic research.

Melanoma classification using light-Fields with morlet scattering transform and CNN: Surface depth as a valuable tool to increase detection rate.

Medical image classification through learning-based approaches has been increasingly used, namely in the discrimination of melanoma. However, for skin lesion classification in general, such methods commonly rely on dermoscopic or other 2D-macro RGB images. This work proposes to exploit beyond conventional 2D image characteristics, by considering a third dimension (depth) that characterises the skin surface rugosity, which can be obtained from light-field images, such as those available in the SKINL2 dataset. To achieve this goal, a processing pipeline was deployed using a morlet scattering transform and a CNN model, allowing to perform a comparison between using 2D information, only 3D information, or both. Results show that discrimination between Melanoma and Nevus reaches an accuracy of 84.00, 74.00 or 94.00% when using only 2D, only 3D, or both, respectively. An increase of 14.29pp in sensitivity and 8.33pp in specificity is achieved when expanding beyond conventional 2D information by also using depth. When discriminating between Melanoma and all other types of lesions (a further imbalanced setting), an increase of 28.57pp in sensitivity and decrease of 1.19pp in specificity is achieved for the same test conditions. Overall the results of this work demonstrate significant improvements over conventional approaches.

Skin lesion classification using features of 3D border lines.

Machine learning algorithms are progressively assuming important roles as computational tools to support clinical diagnosis, namely in the classification of pigmented skin lesions using RGB images. Most current classification methods rely on common 2D image features derived from shape, colour or texture, which does not always guarantee the best results. This work presents a contribution to this field, by exploiting the lesions' border line characteristics using a new dimension - depth, which has not been thoroughly investigated so far. A selected group of features is extracted from the depth information of 3D images, which are then used for classification using a quadratic Support Vector Machine. Despite class imbalance often present in medical image datasets, the proposed algorithm achieves a top geometric mean of 94.87%, comprising 100.00% sensitivity and 90.00% specificity, using only depth information for the detection of Melanomas. Such results show that potential gains can be achieved by extracting information from this often overlooked dimension, which provides more balanced results in terms of sensitivity and specificity than other settings.

Imidazole Processing of Wheat Straw and Eucalyptus Residues-Comparison of Pre-Treatment Conditions and Their Influence on Enzymatic Hydrolysis.

Biomass pre-treatment is a key step in achieving the economic competitiveness of biomass conversion. In the present work, an imidazole pre-treatment process was performed and evaluated using wheat straw and eucalyptus residues as model feedstocks for agriculture and forest-origin biomasses, respectively. Results showed that imidazole is an efficient pre-treatment agent; however, better results were obtained for wheat straw due to the recalcitrant behavior of eucalyptus residues. The temperature had a stronger effect than time on wheat straw pre-treatment but at 160 °C and 4 h, similar results were obtained for cellulose and hemicellulose content from both biomasses (ca. 54% and 24%, respectively). Lignin content in the pre-treated solid was higher for eucalyptus residues (16% vs. 4%), as expected. Enzymatic hydrolysis, applied to both biomasses after different pre-treatments, revealed that results improved with increasing temperature/time for wheat straw. However, these conditions had no influence on the results for eucalyptus residues, with very low glucan to glucose enzymatic hydrolysis yield (93% for wheat straw vs. 40% for eucalyptus residues). Imidazole can therefore be considered as a suitable solvent for herbaceous biomass pre-treatment.

Single-Molecule Super-Resolution Imaging of T-Cell Plasma Membrane CD4 Redistribution upon HIV-1 Binding.

The first step of cellular entry for the human immunodeficiency virus type-1 (HIV-1) occurs through the binding of its envelope protein (Env) with the plasma membrane receptor CD4 and co-receptor CCR5 or CXCR4 on susceptible cells, primarily CD4+ T cells and macrophages. Although there is considerable knowledge of the molecular interactions between Env and host cell receptors that lead to successful fusion, the precise way in which HIV-1 receptors redistribute to sites of virus binding at the nanoscale remains unknown. Here, we quantitatively examine changes in the nanoscale organisation of CD4 on the surface of CD4+ T cells following HIV-1 binding. Using single-molecule super-resolution imaging, we show that CD4 molecules are distributed mostly as either individual molecules or small clusters of up to 4 molecules. Following virus binding, we observe a local 3-to-10-fold increase in cluster diameter and molecule number for virus-associated CD4 clusters. Moreover, a similar but smaller magnitude reorganisation of CD4 was also observed with recombinant gp120. For one of the first times, our results quantify the nanoscale CD4 reorganisation triggered by HIV-1 on host CD4+ T cells. Our quantitative approach provides a robust methodology for characterising the nanoscale organisation of plasma membrane receptors in general with the potential to link spatial organisation to function.

Selective Coordination of Cu2+ and Subsequent Anion Detection Based on a Naphthalimide-Triazine-(DPA)2 Chemosensor.

A new fluorescent chemosensor for copper (II) and subsequent anion sensing was designed and fully characterized. The sensor consisted of a 1,8-naphthalimide core, bearing two terminal dipicolylamine (DPA) receptor units for binding metal cations, and an ethoxyethanol moiety for enhanced water solubility. The DPA units are connected to position 4 of the fluorophore via a triazine-ethylenediamine spacer. Fluorescence titration studies of the chemosensor revealed a high selectivity for Cu2+ over other divalent ions, the emissions were strongly quenched upon binding, and a stability constant of 5.52 log units was obtained. Given the distance from DPA chelating units and the fluorophore, quenching from the Cu2+ complexation suggests an electron transfer or an electronic energy transfer mechanism. Furthermore, the Cu2+-sensor complex proved to be capable of sensing anionic phosphate derivatives through the displacement of the Cu2+ cation, which translated into a full recovery of the luminescence from the naphthalimide. Super-resolution fluorescence microscopy studies performed in HeLa cells showed there was a high intracellular uptake of the chemosensor. Incubation in Cu2+ spiked media revealed a strong fluorescent signal from mitochondria and cell membranes, which is consistent with a high concentration of ATP at these intracellular sites.

Super-beacons: Open-source probes with spontaneous tuneable blinking compatible with live-cell super-resolution microscopy.

Localization-based super-resolution microscopy relies on the detection of individual molecules cycling between fluorescent and non-fluorescent states. These transitions are commonly regulated by high-intensity illumination, imposing constrains to imaging hardware and producing sample photodamage. Here, we propose single-molecule self-quenching as a mechanism to generate spontaneous photoswitching. To demonstrate this principle, we developed a new class of DNA-based open-source super-resolution probes named super-beacons, with photoswitching kinetics that can be tuned structurally, thermally and chemically. The potential of these probes for live-cell compatible super-resolution microscopy without high-illumination or toxic imaging buffers is revealed by imaging interferon inducible transmembrane proteins (IFITMs) at sub-100 nm resolutions.

Reliability of diffusion tensor tractography of facial nerve in cerebello-pontine angle tumours.

AIM OF THE STUDY: This study aimed to verify the accuracy of preoperative visualisation of the facial nerve (FN) by magnetic resonance-based (MR) diffusion tensor imaging-fibre tracking (DTI-FT) with neuronavigation system integration in patients with cerebello-pontine angle (CPA) tumours. CLINICAL RATIONALE FOR THE STUDY: Complete excision with preservation of the FN remains the critical goal of today's vestibular schwannoma (VS) surgery. DTI-FT of the FN with neuronavigation is yet to be fully evaluated, and could make surgery safer. MATERIALS AND METHODS: This was a prospective cohort study in which 38 consecutive patients with a CPA tumour (32 VSs, five meningiomas and one epidermoid cyst) were operated on via the retrosigmoid route from 2013 to 2019. The course of the FN was simulated before surgery using StealthViz and the images were transferred to the Medtronic S7 neuronavigation system. The FN location reconstructed by DTI-FT was verified during the surgery. RESULTS: MR acquisition was inappropriate in three patients (7.9%). DTI-FT correctly predicted the course of the FN in 31 of the 38 patients; the discordance rate was 18.4%. The accuracy of DTI-FT was 81.6% (95% CI: 65.67-92.26), sensitivity 88.57% (95% CI: 73.26-96.80) and positive predictive value was 91.18% (95% CI: 90.17-92.09). The reliability of the neuronavigation-integrated visualisation of the FN did not depend on the tumour size (p = 0.85), but the method was more accurate when the nerve was compact in shape (p = 0.03, area under curve (AUC) 0.87, 95% CI: 0.60-1.00) and in females (p = 0.04, AUC 0.78, 95% CI: 0.56-1.00). Following surgery, 86.5% of the patients presented with useful facial function (House-Brackmann grades I-III). Correct simulation of the FN did not prevent postoperative facial palsy (p = 0.35). CONCLUSIONS: The accuracy of DTI-FT of the FN integrated with neuronavigation remains unsatisfactory. This method does not provide any clinical benefit over non-integrated DTI-FT in terms of nerve function preservation. CLINICAL IMPLICATIONS: Due to the low reliability of the predictions, further technical advances in predicting the course of the FN are awaited by clinicians. However, DTI-FT images in the operating theatre would make tumour excision more comfortable for the surgeon.

Author Correction: TMEM16F activation by Ca2+ triggers plasma membrane expansion and directs PD-1 trafficking.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Fix Your Membrane Receptor Imaging: Actin Cytoskeleton and CD4 Membrane Organization Disruption by Chemical Fixation.

Single-molecule localization microscopy (SMLM) techniques allow near molecular scale resolution (~ 20 nm) as well as precise and robust analysis of protein organization at different scales. SMLM hardware, analytics and probes have been the focus of a variety of studies and are now commonly used in laboratories across the world. Protocol reliability and artifact identification are increasingly seen as important aspects of super-resolution microscopy. The reliability of these approaches thus requires in-depth evaluation so that biological findings are based on solid foundations. Here we explore how different fixation approaches that disrupt or preserve the actin cytoskeleton affect membrane protein organization. Using CD4 as a model, we show that fixation-mediated disruption of the actin cytoskeleton correlates with changes in CD4 membrane organization. We highlight how these artifacts are easy to overlook and how careful sample preparation is essential for extracting meaningful results from super-resolution microscopy.

Automating multimodal microscopy with NanoJ-Fluidics.

Combining and multiplexing microscopy approaches is crucial to understand cellular events, but requires elaborate workflows. Here, we present a robust, open-source approach for treating, labelling and imaging live or fixed cells in automated sequences. NanoJ-Fluidics is based on low-cost Lego hardware controlled by ImageJ-based software, making high-content, multimodal imaging easy to implement on any microscope with high reproducibility. We demonstrate its capacity on event-driven, super-resolved live-to-fixed and multiplexed STORM/DNA-PAINT experiments.

Phytochemical profile of genotypes of Euterpe edulis Martius - Juçara palm fruits.

Juçara fruit (Euterpe edulis) has received attention due to its similarities to Euterpe oleracea (Açaí). The aim of this study was to evaluate the cytotoxicity, bioactive compounds, antioxidant capacities and chemopreventive activities of the fruit pulps of six populations of E. edulis (J1-J6) and one population of E. espiritosantense from different ecological regions. ESI(-)-FT-ICR-MS was used to evaluate the pulp composition. The varieties J1 and J4 presented higher polyphenol contents, while J2 and J5 showed higher anthocyanin contents. ESI-FT-ICR MS identified cyanidin-3-rutinoside (J1, J2, J3, J4, J5, J7), protocatechuic acid, methylhydroxybenzoate hexoside and rutin (J1 to J7) and malvidin-glicoside (J2 to J5). The J2, J3, J4, J5 and J6 samples inhibited inducible nitric oxide synthase (iNOS). The chemoprevention biomarker quinone reductase was significantly induced by J6. Pulp from plants J3, J4, J6 and J7 significantly reduced the inflammatory cytokine TNF-α, and J6 was selected as having the most potential for cultivation and consumption.

TMEM16F activation by Ca2+ triggers plasma membrane expansion and directs PD-1 trafficking.

TMEM16F is a Ca2+ -gated ion channel that is required for Ca2+ -activated phosphatidylserine exposure on the surface of many eukaryotic cells. TMEM16F is widely expressed and has roles in platelet activation during blood clotting, bone formation and T cell activation. By combining microscopy and patch clamp recording we demonstrate that activation of TMEM16F by Ca2+ ionophores in Jurkat T cells triggers large-scale surface membrane expansion in parallel with phospholipid scrambling. With continued ionophore application,TMEM16F-expressing cells then undergo extensive shedding of ectosomes. The T cell co-receptor PD-1 is selectively incorporated into ectosomes. This selectivity depends on its transmembrane sequence. Surprisingly, cells lacking TMEM16F not only fail to expand surface membrane in response to elevated cytoplasmic Ca2+, but instead undergo rapid massive endocytosis with PD-1 internalisation. These results establish a new role for TMEM16F as a regulator of Ca2+ activated membrane trafficking.

Light Field Image Dataset of Skin Lesions.

Light field imaging technology has been attracting increasing interest because it enables capturing enriched visual information and expands the processing capabilities of traditional 2D imaging systems. Dense multiview, accurate depth maps and multiple focus planes are examples of different types of visual information enabled by light fields. This technology is also emerging in medical imaging research, like dermatology, allowing to find new features and improve classification algorithms, namely those based on machine learning approaches. This paper presents a contribution for the research community, in the form of a publicly available light field image dataset of skin lesions (named SKINL2 v1.0). This dataset contains 250 light fields, captured with a focused plenoptic camera and classified into eight clinical categories, according to the type of lesion. Each light field is comprised of 81 different views of the same lesion. The database also includes the dermatoscopic image of each lesion. A representative subset of 17 central view images of the light fields is further characterised in terms of spatial information (SI), colourfulness (CF) and compressibility. This dataset has high potential for advancing medical imaging research and development of new classification algorithms based on light fields, as well as in clinically-oriented dermatology studies.

NanoJ: a high-performance open-source super-resolution microscopy toolbox.

Super-resolution microscopy (SRM) has become essential for the study of nanoscale biological processes. This type of imaging often requires the use of specialised image analysis tools to process a large volume of recorded data and extract quantitative information. In recent years, our team has built an open-source image analysis framework for SRM designed to combine high performance and ease of use. We named it NanoJ-a reference to the popular ImageJ software it was developed for. In this paper, we highlight the current capabilities of NanoJ for several essential processing steps: spatio-temporal alignment of raw data (NanoJ-Core), super-resolution image reconstruction (NanoJ-SRRF), image quality assessment (NanoJ-SQUIRREL), structural modelling (NanoJ-VirusMapper) and control of the sample environment (NanoJ-Fluidics). We expect to expand NanoJ in the future through the development of new tools designed to improve quantitative data analysis and measure the reliability of fluorescent microscopy studies.

Stability and Ligand Promiscuity of Type A Carbohydrate-binding Modules Are Illustrated by the Structure of Spirochaeta thermophila StCBM64C.

Deconstruction of cellulose, the most abundant plant cell wall polysaccharide, requires the cooperative activity of a large repertoire of microbial enzymes. Modular cellulases contain non-catalytic type A carbohydrate-binding modules (CBMs) that specifically bind to the crystalline regions of cellulose, thus promoting enzyme efficacy through proximity and targeting effects. Although type A CBMs play a critical role in cellulose recycling, their mechanism of action remains poorly understood. Here we produced a library of recombinant CBMs representative of the known diversity of type A modules. The binding properties of 40 CBMs, in fusion with an N-terminal GFP domain, revealed that type A CBMs possess the ability to recognize different crystalline forms of cellulose and chitin over a wide range of temperatures, pH levels, and ionic strengths. A Spirochaeta thermophila CBM64, in particular, displayed plasticity in its capacity to bind both crystalline and soluble carbohydrates under a wide range of extreme conditions. The structure of S. thermophila StCBM64C revealed an untwisted, flat, carbohydrate-binding interface comprising the side chains of four tryptophan residues in a co-planar linear arrangement. Significantly, two highly conserved asparagine side chains, each one located between two tryptophan residues, are critical to insoluble and soluble glucan recognition but not to bind xyloglucan. Thus, CBM64 compact structure and its extended and versatile ligand interacting platform illustrate how type A CBMs target their appended plant cell wall-degrading enzymes to a diversity of recalcitrant carbohydrates under a wide range of environmental conditions.

K63-Linked Ubiquitination Targets Toxoplasma gondii for Endo-lysosomal Destruction in IFNγ-Stimulated Human Cells.

Toxoplasma gondii is the most common protozoan parasitic infection in man. Gamma interferon (IFNγ) activates haematopoietic and non-haematopoietic cells to kill the parasite and mediate host resistance. IFNγ-driven host resistance pathways and parasitic virulence factors are well described in mice, but a detailed understanding of pathways that kill Toxoplasma in human cells is lacking. Here we show, that contrary to the widely held belief that the Toxoplasma vacuole is non-fusogenic, in an immune-stimulated environment, the vacuole of type II Toxoplasma in human cells is able to fuse with the host endo-lysosomal machinery leading to parasite death by acidification. Similar to murine cells, we find that type II, but not type I Toxoplasma vacuoles are targeted by K63-linked ubiquitin in an IFNγ-dependent manner in non-haematopoetic primary-like human endothelial cells. Host defence proteins p62 and NDP52 are subsequently recruited to the type II vacuole in distinct, overlapping microdomains with a loss of IFNγ-dependent restriction in p62 knocked down cells. Autophagy proteins Atg16L1, GABARAP and LC3B are recruited to <10% of parasite vacuoles and show no parasite strain preference, which is consistent with inhibition and enhancement of autophagy showing no effect on parasite replication. We demonstrate that this differs from HeLa human epithelial cells, where type II Toxoplasma are restricted by non-canonical autophagy leading to growth stunting that is independent of lysosomal acidification. In contrast to mouse cells, human vacuoles do not break. In HUVEC, the ubiquitinated vacuoles are targeted for destruction in acidified LAMP1-positive endo-lysosomal compartments. Consequently, parasite death can be prevented by inhibiting host ubiquitination and endosomal acidification. Thus, K63-linked ubiquitin recognition leading to vacuolar endo-lysosomal fusion and acidification is an important, novel virulence-driven Toxoplasma human host defence pathway.