Replication of SARS-CoV-2 Omicron BA.2 variant in ex vivo cultures of the human upper and lower respiratory tract.

BACKGROUND: The Omicron BA.2 sublineage has replaced BA.1 worldwide and has comparable levels of immune evasion to BA.1. These observations suggest that the increased transmissibility of BA.2 cannot be explained by the antibody evasion. METHODS: Here, we characterized the replication competence and respiratory tissue tropism of three Omicron variants (BA.1, BA.1.1, BA.2), and compared these with the wild-type virus and Delta variant, in human nasal, bronchial and lung tissues cultured ex vivo. FINDINGS: BA.2 replicated more efficiently in nasal and bronchial tissues at 33°C than wild-type, Delta and BA.1. Both BA.2 and BA.1 had higher replication competence than wild-type and Delta viruses in bronchial tissues at 37°C. BA.1, BA.1.1 and BA.2 replicated at a lower level in lung parenchymal tissues compared to wild-type and Delta viruses. INTERPRETATION: Higher replication competence of Omicron BA.2 in the human upper airway at 33°C than BA.1 may be one of the reasons to explain the current advantage of BA.2 over BA.1. A lower replication level of the tested Omicron variants in human lung tissues is in line with the clinical manifestations of decreased disease severity of patients infected with the Omicron strains compared with other ancestral strains. FUNDING: This work was supported by US National Institute of Allergy and Infectious Diseases and the Theme-Based Research Scheme under University Grants Committee of Hong Kong Special Administrative Region, China.

SARS-CoV-2 Omicron variant replication in human bronchus and lung ex vivo.

The emergence of SARS-CoV-2 variants of concern with progressively increased transmissibility between humans is a threat to global public health. The Omicron variant of SARS-CoV-2 also evades immunity from natural infection or vaccines1, but it is unclear whether its exceptional transmissibility is due to immune evasion or intrinsic virological properties. Here we compared the replication competence and cellular tropism of the wild-type virus and the D614G, Alpha (B.1.1.7), Beta (B.1.351), Delta (B.1.617.2) and Omicron (B.1.1.529) variants in ex vivo explant cultures of human bronchi and lungs. We also evaluated the dependence on TMPRSS2 and cathepsins for infection. We show that Omicron replicates faster than all other SARS-CoV-2 variants studied in the bronchi but less efficiently in the lung parenchyma. All variants of concern have similar cellular tropism compared to the wild type. Omicron is more dependent on cathepsins than the other variants of concern tested, suggesting that the Omicron variant enters cells through a different route compared with the other variants. The lower replication competence of Omicron in the human lungs may explain the reduced severity of Omicron that is now being reported in epidemiological studies, although determinants of severity are multifactorial. These findings provide important biological correlates to previous epidemiological observations.

High-Throughput, Label-Free and Slide-Free Histological Imaging by Computational Microscopy and Unsupervised Learning.

Rapid and high-resolution histological imaging with minimal tissue preparation has long been a challenging and yet captivating medical pursuit. Here, the authors propose a promising and transformative histological imaging method, termed computational high-throughput autofluorescence microscopy by pattern illumination (CHAMP). With the assistance of computational microscopy, CHAMP enables high-throughput and label-free imaging of thick and unprocessed tissues with large surface irregularity at an acquisition speed of 10 mm2 /10 s with 1.1-µm lateral resolution. Moreover, the CHAMP image can be transformed into a virtually stained histological image (Deep-CHAMP) through unsupervised learning within 15 s, where significant cellular features are quantitatively extracted with high accuracy. The versatility of CHAMP is experimentally demonstrated using mouse brain/kidney and human lung tissues prepared with various clinical protocols, which enables a rapid and accurate intraoperative/postoperative pathological examination without tissue processing or staining, demonstrating its great potential as an assistive imaging platform for surgeons and pathologists to provide optimal adjuvant treatment.

Use of metabolomics to identify strategies to improve and prolong ex vivo lung perfusion for lung transplants.

BACKGROUND: Normothermic ex vivo lung perfusion (EVLP) allows for functional assessment of donor lungs; thus has increased the use of marginal lungs for transplantation. To extend EVLP for advanced organ reconditioning and regenerative interventions, cellular metabolic changes need to be understood. We sought to comprehensively characterize the dynamic metabolic changes of the lungs during EVLP, and to identify strategies to improve EVLP. METHODS: Human donor lungs (n = 50) were assessed under a 4-hour Toronto EVLP protocol. EVLP perfusate was sampled at first (EVLP-1h) and fourth hour (EVLP-4h) of perfusion and were submitted for mass spectrometry-based untargeted metabolic profiling. Differentially expressed metabolites between the 2 timepoints were identified and analyzed from the samples of lungs transplanted post-EVLP (n = 42) to determine the underlying molecular mechanisms. RESULTS: Of the total 312 detected metabolites, 84 were up-regulated and 103 were down-regulated at EVLP-4h relative to 1h (FDR adjusted p < .05, fold change ≥ |1.1|). At EVLP-4h, markedly decreased energy substrates were observed, accompanied by the increase in fatty acid ß-oxidation. Concurrently, accumulation of amino acids and nucleic acids was evident, indicative of increased protein and nucleotide catabolism. The uniform decrease in free lysophospholipids and polyunsaturated fatty acids at EVLP-4h suggests cell membrane remodeling. CONCLUSIONS: Untargeted metabolomics revealed signs of energy substrate consumption and metabolic by-product accumulation under current EVLP protocols. Strategies to supplement nutrients and to maintain homeostasis will be vital in improving the current clinical practice and prolonging organ perfusion for therapeutic application to further enhance donor lung utilization.

Deep-learning-assisted biophysical imaging cytometry at massive throughput delineates cell population heterogeneity.

The association of the intrinsic optical and biophysical properties of cells to homeostasis and pathogenesis has long been acknowledged. Defining these label-free cellular features obviates the need for costly and time-consuming labelling protocols that perturb the living cells. However, wide-ranging applicability of such label-free cell-based assays requires sufficient throughput, statistical power and sensitivity that are unattainable with current technologies. To close this gap, we present a large-scale, integrative imaging flow cytometry platform and strategy that allows hierarchical analysis of intrinsic morphological descriptors of single-cell optical and mass density within a population of millions of cells. The optofluidic cytometry system also enables the synchronous single-cell acquisition of and correlation with fluorescently labeled biochemical markers. Combined with deep neural network and transfer learning, this massive single-cell profiling strategy demonstrates the label-free power to delineate the biophysical signatures of the cancer subtypes, to detect rare populations of cells in the heterogeneous samples (10-5), and to assess the efficacy of targeted therapeutics. This technique could spearhead the development of optofluidic imaging cell-based assays that stratify the underlying physiological and pathological processes based on the information-rich biophysical cellular phenotypes.

New T1 classification.

The IASLC staging and Prognostic Factor Committee proposed new changes to the descriptors for the 8th edition of the Tumour Node Metastasis Staging for Lung Cancer. The T1 descriptor changes include (1) T1 tumours are subclassified into T1a (< 1 cm), T1b (> 1 to < 2 cm), T1c (> 2 to < 3 cm). The corresponding changes are introduced to the overall staging: T1aN0M0 = Stage IA1; T1bN0M0 = Stage IA2; T1cN0M0 = Stage IA3. (2) The introduction of the pathological entities Adenocarcinoma-In-Situ (AIS), Minimally Invasive Adenocarcinoma, and Lepidic Predominant Adenocarcinoma. The corresponding changes on the T descriptor are as follows: Adenocarcinoma-in situ is coded as Tis (AIS); Minimally Invasive Adenocarcinoma is coded as T1a(mi). In this review, the basis for these changes will be described, and the implications on clinical practice will be discussed.