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While the primary sequences of human proteins have been cataloged for over a decade, determining how these are organized into a dynamic collection of multiprotein assemblies, with structures and functions spanning biological scales, is an ongoing venture. Systematic and data-driven analyses of these higher-order structures are emerging, facilitating the discovery and understanding of cellular phenotypes. At present, knowledge of protein localization and function has been primarily derived from manual annotation and curation in resources such as the Gene Ontology, which are biased toward richly annotated genes in the literature. Here, we envision a future powered by data-driven mapping of protein assemblies. These maps can capture and decode cellular functions through the integration of protein expression, localization, and interaction data across length scales and timescales. In this review, we focus on progress toward constructing integrated cell maps that accelerate the life sciences and translational research.

The spatial organization of molecules in a cell is essential for their functions. While current methods focus on discerning tissue architecture, cell-cell interactions, and spatial expression patterns, they are limited to the multicellular scale. We present Bento, a Python toolkit that takes advantage of single-molecule information to enable spatial analysis at the subcellular scale. Bento ingests molecular coordinates and segmentation boundaries to perform three analyses: defining subcellular domains, annotating localization patterns, and quantifying gene-gene colocalization. We demonstrate MERFISH, seqFISH + , Molecular Cartography, and Xenium datasets. Bento is part of the open-source Scverse ecosystem, enabling integration with other single-cell analysis tools.

Abstract The spatial organization of molecules in a cell is essential for their functions. While current methods focus on discerning tissue architecture, cell–cell interactions, and spatial expression patterns, they are limited to the multicellular scale. We present Bento, a Python toolkit that takes advantage of single-molecule information to enable spatial analysis at the subcellular scale. Bento ingests molecular coordinates and segmentation boundaries to perform three analyses: defining subcellular domains, annotating localization patterns, and quantifying gene–gene colocalization. We demonstrate MERFISH, seqFISH + , Molecular Cartography, and Xenium datasets. Bento is part of the open-source Scverse ecosystem, enabling integration with other single-cell analysis tools.

Abstract Humidity sensors are used in many applications. The design of fast sensors that can operate in explosive environments is a difficult task. Therefore, current research efforts aim at combining reliability, sensitivity and high sensing speed. The use of structured ultrathin hydrogels perfectly meets these requirements. Nanostructures are directly fabricated with a two‐photon‐polymerisation (2PP) 3D printer to use them as templates for hydrogels. After the 3D printing multiple templates are coated with ultrathin films of poly(2‐hydroxyethyl‐methacrylate) (pHEMA) using initiated chemical vapor deposition (iCVD). p(HEMA) is a humidity responsive hydrogel which changes its thickness by orders of magnitude depending on the ambient conditions. The 3D printed structures are optimized to give both a fast response time, and an optical read‐out method for visible wavelengths. Upon hydrogel swelling, the height of the nanostructure pillars increases, keeping their periodicity constant. This induces a change in intensity of the first ‐order refraction peak, which can be easily measured also at low humidity levels. The humidity response of the nanostructures is measured and an influence for different hydrogel thicknesses and humidity flow rates is observed. The ultrathin film with the lowest thickness of 50 nm shows the fastest response to relative humidity, which is much faster than commercial sensors with 8 s response time.

The Consortium for Top-Down Proteomics (CTDP) proposes a standardized notation, ProForma, for writing the sequence of fully characterized proteoforms. ProForma provides a means to communicate any proteoform by writing the amino acid sequence using standard one-letter notation and specifying modifications or unidentified mass shifts within brackets following certain amino acids. The notation is unambiguous, human-readable, and can easily be parsed and written by bioinformatic tools. This system uses seven rules and supports a wide range of possible use cases, ensuring compatibility and reproducibility of proteoform annotations. Standardizing proteoform sequences will simplify storage, comparison, and reanalysis of proteomic studies, and the Consortium welcomes input and contributions from the research community on the continued design and maintenance of this standard.

Today, humidity sensors have become an integral part of the daily lives. In particular, humidity sensors using an electronic measuring principle have become the standard. Although these sensors have proven to be a stable measurement method, they have some disadvantages, such as their long response time or the danger of using them in explosive environments. This work introduces photonic crystals as an alternative optical measurement approach. The novel technology of ultra‐fast two‐photon polymerisation printing is combined with a thin‐film deposition process, namely iCVD. This allows to print large area high‐precision 3D templates, which are subsequently coated with a humidity responsive hydrogel thin film (p(HEMA) of 20 nm.The limits of 2PP technology are being pushed allowing the production ofs table and periodic large‐area 3D structures. The flexible customization of hydrogels for ambient conditions make them exceptionally promising for a wide range of sensing applications. Additionally, optical methods for measuring humidity seem to be an excellent alternative to overcome the limitations for current state of the art humidity sensors. The optical detection of changes in ambient air humidity is achieved by observing color changes of the printed structure within the visible wavelength range. [ABSTRACT FROM AUTHOR]

The cell cycle, over which cells grow and divide, is a fundamental process of life. Its dysregulation has devastating consequences, including cancer.sup.1-3. The cell cycle is driven by precise regulation of proteins in time and space, which creates variability between individual proliferating cells. To our knowledge, no systematic investigations of such cell-to-cell proteomic variability exist. Here we present a comprehensive, spatiotemporal map of human proteomic heterogeneity by integrating proteomics at subcellular resolution with single-cell transcriptomics and precise temporal measurements of individual cells in the cell cycle. We show that around one-fifth of the human proteome displays cell-to-cell variability, identify hundreds of proteins with previously unknown associations with mitosis and the cell cycle, and provide evidence that several of these proteins have oncogenic functions. Our results show that cell cycle progression explains less than half of all cell-to-cell variability, and that most cycling proteins are regulated post-translationally, rather than by transcriptomic cycling. These proteins are disproportionately phosphorylated by kinases that regulate cell fate, whereas non-cycling proteins that vary between cells are more likely to be modified by kinases that regulate metabolism. This spatially resolved proteomic map of the cell cycle is integrated into the Human Protein Atlas and will serve as a resource for accelerating molecular studies of the human cell cycle and cell proliferation. Spatial and temporal variations among individual human cell proteomes are comprehensively mapped across the cell cycle using proteomic imaging and transcriptomics., Author(s): Diana Mahdessian [sup.1] , Anthony J. Cesnik [sup.1] [sup.2] [sup.3] , Christian Gnann [sup.1] [sup.3] , Frida Danielsson [sup.1] , Lovisa Stenström [sup.1] , Muhammad Arif [sup.1] , Cheng [...]

Abstract The nucleolus is essential for ribosome biogenesis and is involved in many other cellular functions. We performed a systematic spatiotemporal dissection of the human nucleolar proteome using confocal microscopy. In total, 1,318 nucleolar proteins were identified; 287 were localized to fibrillar components, and 157 were enriched along the nucleoplasmic border, indicating a potential fourth nucleolar subcompartment: the nucleoli rim. We found 65 nucleolar proteins (36 uncharacterized) to relocate to the chromosomal periphery during mitosis. Interestingly, we observed temporal partitioning into two recruitment phenotypes: early (prometaphase) and late (after metaphase), suggesting phase‐specific functions. We further show that the expression of MKI67 is critical for this temporal partitioning. We provide the first proteome‐wide analysis of intrinsic protein disorder for the human nucleolus and show that nucleolar proteins in general, and mitotic chromosome proteins in particular, have significantly higher intrinsic disorder level compared to cytosolic proteins. In summary, this study provides a comprehensive and essential resource of spatiotemporal expression data for the nucleolar proteome as part of the Human Protein Atlas.

The Heidenhain Variant of Creutzfeldt–Jakob disease (CJD) is an uncommon early clinical syndrome of the otherwise regular sporadic CJD, which belongs to the group of prion diseases caused by a transmissible agent, the misfolded form of the prion protein. The most characteristic symptoms of CJD are rapidly progressive cognitive impairment, typical motor manifestations and mental and behavioural changes. Conversely, in the Heidenhain Variant, different kinds of visual disturbances are observed at onset due to microvacuolar spongiform degeneration or, less frequently, confluent spongiform changes in the parieto-occipital area, detectable through brain MRI with hyperintensity in T2-FLAIR or DWI in the same areas. Since this an extremely rare condition with a heterogeneous clinical presentation, it may easily be misdiagnosed with other diseases at the earlier stages. Here, we describe the case of a patient initially diagnosed with posterior reversible encephalopathy syndrome (PRES), presenting with visual disturbances and headache at onset in a context of poorly controlled arterial hypertension. Subsequently, a rapid worsening of cognitive decline, associated with myoclonus and startle reaction led to further investigations, shifting the diagnosis toward a rapidly evolving neurodegenerative form. This hypothesis was also supported by EEG traces, MRI and CSF analysis. Finally, the clinical–instrumental evolution confirmed the diagnosis of Heidenhain Variant of CJD.

Rare earth elements have been tested in control of plant diseases. Lanthanum (La) was tested in the control of Alternaria solani (in vitro) and tomato early blight (in vivo) using the concentration 0; 0.1; 0.2; 0.4 and 0.8 g L-1. In vitro, the concentration were diluted in V8 culture medium and evaluated for mycelial growth rate index (MGRI) and pathogen sporulation. In vivo, 24 hours after the application of concentration was inoculate the pathogen and 24 hours after the inoculation, leaflets were collected for quantification, the specific catalytic activity and guaiacol peroxidase. The severity of tomato early blight were also analyzed. As 0.27 and 0.28 g L-1 reduces 28% and 50% the MGRI and the sporulation, respectively. Peroxidase and catalase activity was increased by 298% and 151% in tomato treated with 0.5 and 0.4 g L-1de La, respectively. In vivo reduces AUDPC 70% when was applied 0.27 g L-1 La. Lanthanum can be used as resistance inducer in controlling tomato early blight.

Femtosecond laser spectroscopy has contributed to our understanding of structure and function of matter. Here, the authors explore the applicability of superfluid helium nanodroplets as a sample preparation method that allows investigation of previously inaccessible classes of tailor-made or fragile molecular systems.

INTRODUCTION: The molecular mechanisms underlying aggressive versus indolent disease are not fully understood. Recent research has implicated a class of molecules known as long noncoding RNAs (lncRNAs) in tumorigenesis and progression of cancer. Our objective was to discover lncRNAs that differentiate aggressive and indolent prostate cancers. METHODS: We analyzed paired tumor and normal tissues from six aggressive Gleason score (GS) 8-10 and six indolent GS 6 prostate cancers. Extracted RNA was split for poly(A)+ and ribosomal RNA depletion library preparations, followed byRNA sequencing (RNA-Seq) using an Illumina HiSeq 2000. We developed an RNA-Seq data analysis pipeline to discover and quantify these molecules. Candidate lncRNAs were validated using RT-qPCR on 87 tumor tissue samples: 28 (GS 6), 28 (GS 3+4), 6 (GS 4+3), and 25 (GS 8-10). Statistical correlations between lncRNAs and clinicopathologic variables were tested using ANOVA. RESULTS: The 43 differentially expressed (DE) lncRNAs between aggressive and indolent prostate cancers included 12 annotated and 31 novel lncRNAs. The top six DE lncRNAs were selected based on large, consistent fold-changes in the RNA-Seq results. Three of these candidates passed RT-qPCR validation, including AC009014.3 (P < .001 in tumor tissue) and a newly discovered X-linked lncRNA named XPLAID (P = .049 in tumor tissue and P = .048 in normal tissue). XPLAID and AC009014.3 show promise as prognostic biomarkers. CONCLUSIONS: We discovered several dozen lncRNAs that distinguish aggressive and indolent prostate cancers, of which four were validated using RT-qPCR. The investigation into their biology is ongoing.