Bento: a toolkit for subcellular analysis of spatial transcriptomics data.

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.

Computational cell-cell interaction technologies drive mechanistic and biomarker discovery in the tumor microenvironment.

Complex networks of cell-cell interactions (CCIs) within the tumor microenvironment (TME) play a crucial role in cancer persistence. These communication axes represent prime targets for therapeutic intervention, but our incomplete understanding of the cellular heterogeneity and interacting partners within the TME remains a stubborn barrier to complete drug responses. This review outlines recent advances in the study of CCIs that leverage single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) technologies that can clarify TME dynamics. We anticipate that these strategies will promote discovery of CCIs critical to the tumor-immune interface and will, by extension, expand the repertoire of druggable tumor biomarkers.

De novo design of potent and resilient hACE2 decoys to neutralize SARS-CoV-2.

We developed a de novo protein design strategy to swiftly engineer decoys for neutralizing pathogens that exploit extracellular host proteins to infect the cell. Our pipeline allowed the design, validation, and optimization of de novo human angiotensin-converting enzyme 2 (hACE2) decoys to neutralize severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The best monovalent decoy, CTC-445.2, bound with low nanomolar affinity and high specificity to the receptor-binding domain (RBD) of the spike protein. Cryo-electron microscopy (cryo-EM) showed that the design is accurate and can simultaneously bind to all three RBDs of a single spike protein. Because the decoy replicates the spike protein target interface in hACE2, it is intrinsically resilient to viral mutational escape. A bivalent decoy, CTC-445.2d, showed ~10-fold improvement in binding. CTC-445.2d potently neutralized SARS-CoV-2 infection of cells in vitro, and a single intranasal prophylactic dose of decoy protected Syrian hamsters from a subsequent lethal SARS-CoV-2 challenge.

De novo design of ACE2 protein decoys to neutralize SARS-CoV-2.

There is an urgent need for the ability to rapidly develop effective countermeasures for emerging biological threats, such as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that causes the ongoing coronavirus disease 2019 (COVID-19) pandemic. We have developed a generalized computational design strategy to rapidly engineer de novo proteins that precisely recapitulate the protein surface targeted by biological agents, like viruses, to gain entry into cells. The designed proteins act as decoys that block cellular entry and aim to be resilient to viral mutational escape. Using our novel platform, in less than ten weeks, we engineered, validated, and optimized de novo protein decoys of human angiotensin-converting enzyme 2 (hACE2), the membrane-associated protein that SARS-CoV-2 exploits to infect cells. Our optimized designs are hyperstable de novo proteins (∼18-37 kDa), have high affinity for the SARS-CoV-2 receptor binding domain (RBD) and can potently inhibit the virus infection and replication in vitro. Future refinements to our strategy can enable the rapid development of other therapeutic de novo protein decoys, not limited to neutralizing viruses, but to combat any agent that explicitly interacts with cell surface proteins to cause disease.

Development and content validity of the Lupus Foundation of America rapid evaluation of activity in lupus (LFA-REAL™): a patient-reported outcome measure for lupus disease activity.

BACKGROUND/PURPOSE: The LFA REAL™ is a measurement system for evaluating lupus disease activity from both clinician and patient perspectives. Patients' viewpoints are captured using a patient-reported outcome (PRO) questionnaire. A series of visual analog scales are designed to rate disease severity and progress over the past 4 weeks. Brief instructions guide the patient to distinguish between active, potentially reversible symptoms and chronic pain or discomfort that are more likely due to damage. Beyond its simplicity and efficiency, the PRO can provide versatile assessments from a global, organ-based, and symptom-specific level. This paper describes the patient-centered approach used to evaluate the content validity of the LFA-REAL PRO. METHODS: The PRO was developed in accordance with FDA guidance. A two-phase qualitative study was performed with 25 lupus patients, 10 who participated in concept elicitation (Phase 1) and 15 in cognitive debriefing interviews (Phase 2). Qualitative data were analyzed using ATLAS.ti software v7.5. Upon completion of the interviews, participants completed the draft PRO and additional measures to characterize the sample. RESULTS: The mean age of participants was 45.6 and 88% were female, as expected in a lupus population. The mean SF-36 physical component score was 29.8 and the mean mental component score was 46.4. Phase 1 elicited symptom saturation and mapping of the draft PRO. Fatigue was reported by 100% of patients, highlighting its importance as a measurable domain. Additionally, 100% of patients spontaneously mentioned arthritis, which may be more important to this group than previously estimated, substantiating the approach of this PRO to break down components of arthritis into joint pain, stiffness, and swelling. Shortness of breath and fever were reported more frequently than expected. Phase 2 data demonstrated that participants found the instrument easy to use and offered recommendations to improve clarity, leading to adjustments in wording and formatting. CONCLUSIONS: Results suggest that the LFA-REAL PRO has content validity and, with some modifications suggested by participants, is ready for quantitative validation, including tests of reliability, validity, responsiveness to change, and performance relative to other PROs used in lupus trials. After validation, the LFA-REAL system is intended for use in clinical practice and research.

Preliminary test of the LFA rapid evaluation of activity in lupus (LFA-REAL): an efficient outcome measure correlates with validated instruments.

OBJECTIVE: Current disease activity measures for systemic lupus erythematosus (SLE) are difficult to score or interpret and problematic for use in clinical practice. Lupus Foundation of America (LFA)-Rapid Evaluation of Activity in Lupus (REAL) is a pilot application composed of anchored visual analogue scores (0-100 mm each) for each organ affected by lupus. This study evaluated the use of LFA-REAL in capturing SLE disease activity. METHODS: In a preliminary test of LFA-REAL, this simplified, organ-based system was compared with the most widely used outcome measures in clinical trials, the British Isles Lupus Assessment Group 2004 Index (BILAG), the SLE Disease Activity Index (SLEDAI) and the Safety of Estrogens in Lupus Erythematosus National Assessment (SELENA) SLEDAI Physician's Global Assessment (SS-PGA). The level of agreement was analysed using Spearman rank correlations. RESULTS: 91 patients with SLE with mild to severe disease activity were evaluated, their median SLEDAI score was 4.0 (range 0-28) and BILAG score 8.0 (0-32). The median SS-PGA was 38 mm (4-92) versus the total REAL 50 mm (0-268), which expands in range by additive organ scores. Thirty-three patients had moderate to severe disease activity (≥1.5 on SS-PGA landmarks). The median SS-PGA score of this group was 66 mm (50-92) versus median REAL score of 100 mm (59-268), confirming ability to detect a wider distribution of scores at higher disease activity. Total REAL correlated with SLEDAI, BILAG and SS-PGA (correlation coefficient=0.816, 0.933 and 0.903, respectively; p<0.001 for all). Individual LFA-REAL organ scores for musculoskeletal and mucocutaneous also correlated with corresponding BILAG domain scores (correlation coefficient=0.925 and 0.934, p<0.001). CONCLUSIONS: In this preliminary exercise, there were strong correlations between LFA-REAL and validated lupus disease activity indices. Further development may be valuable for consistent scoring in clinical trials, grading optimal assessment of change in disease activity and reliable monitoring of patients in practice.