A universal reagent for detection of emerging diseases using bioengineered multifunctional yeast nanofragments.

Accurate and early detection of biomarkers provides the molecular evidence for disease management, allowing prompt actions and timely treatments to save lives. Multivalent biomolecular interactions between the probe and biomarker as well as controlled probe orientation on material surfaces are keys for highly sensitive detection. Here we report the bioengineering of programmable and multifunctional nanoprobes, which can provide rapid, specific and highly sensitive detection of emerging diseases in a range of widely used diagnostic systems. These nanoprobes composed of nanosized cell wall fragments, termed as synthetic bionanofragments (SynBioNFs), are generated by the fragmentation of genetically programmed yeast cells. SynBioNFs display multiple copies of biomolecules for high-affinity target binding and molecular handles for the precisely orientated attachment on surfaces used in diagnostic platforms. SynBioNFs are demonstrated for the capture and detection of SARS-CoV-2 virions using multiple diagnostic platforms, including surface-enhanced Raman scattering, fluorescence, electrochemical and colorimetric-based lateral flow systems with sensitivity comparable with the gold-standard reverse-transcription quantitative polymerase chain reaction.

A Multiplexed SERS Microassay for Accurate Detection of SARS-CoV-2 and Variants of Concern.

Severe acute respiratory syndrome coronavirus 2 variants play an important role in predicting patient outcome during postinfection, and with growing fears of COVID-19 reservoirs in domestic and wild animals, it is necessary to adapt detection systems for variant detection. However, variant-specific detection remains challenging. Surface-enhanced Raman scattering is a sensitive and multiplexing technique that allows the simultaneous detection of multiple targets for accurate identification. Here we propose the development of a multiplex SERS microassay to detect both the spike and nucleocapsid structural proteins of SARS-CoV-2. The designed SERS microassay integrates gold-silver hollow nanobox barcodes and electrohydrodynamically induced nanomixing which in combination enables highly specific and sensitive detection of SARS-CoV-2 and the S-protein epitopes to delineate between ancestral prevariant strains with the newer variants of concern, Delta and Omicron. The microassay allows detection from as low as 20 virus/µL and 50 pg/mL RBD protein and can clearly identify the virus among infected versus healthy nasopharyngeal swabs, with the potential to identify between variants. The detection of both S- and N-proteins of SARS-CoV-2 and the differentiation of variants on the SERS microassay can aid the early detection of COVID-19 to reduce transmission rates and lead into adequate treatments for those severely affected by the virus.

Next-Generation Molecular Discovery: From Bottom-Up In Vivo and In Vitro Approaches to In Silico Top-Down Approaches for Therapeutics Neogenesis.

Protein and drug engineering comprises a major part of the medical and research industries, and yet approaches to discovering and understanding therapeutic molecular interactions in biological systems rely on trial and error. The general approach to molecular discovery involves screening large libraries of compounds, proteins, or antibodies, or in vivo antibody generation, which could be considered "bottom-up" approaches to therapeutic discovery. In these bottom-up approaches, a minimal amount is known about the therapeutics at the start of the process, but through meticulous and exhaustive laboratory work, the molecule is characterised in detail. In contrast, the advent of "big data" and access to extensive online databases and machine learning technologies offers promising new avenues to understanding molecular interactions. Artificial intelligence (AI) now has the potential to predict protein structure at an unprecedented accuracy using only the genetic sequence. This predictive approach to characterising molecular structure-when accompanied by high-quality experimental data for model training-has the capacity to invert the process of molecular discovery and characterisation. The process has potential to be transformed into a top-down approach, where new molecules can be designed directly based on the structure of a target and the desired function, rather than performing screening of large libraries of molecular variants. This paper will provide a brief evaluation of bottom-up approaches to discovering and characterising biological molecules and will discuss recent advances towards developing top-down approaches and the prospects of this.

A digital single-molecule nanopillar SERS platform for predicting and monitoring immune toxicities in immunotherapy.

The introduction of immune checkpoint inhibitors has demonstrated significant improvements in survival for subsets of cancer patients. However, they carry significant and sometimes life-threatening toxicities. Prompt prediction and monitoring of immune toxicities have the potential to maximise the benefits of immune checkpoint therapy. Herein, we develop a digital nanopillar SERS platform that achieves real-time single cytokine counting and enables dynamic tracking of immune toxicities in cancer patients receiving immune checkpoint inhibitor treatment - broader applications are anticipated in other disease indications. By analysing four prospective cytokine biomarkers that initiate inflammatory responses, the digital nanopillar SERS assay achieves both highly specific and highly sensitive cytokine detection down to attomolar level. Significantly, we report the capability of the assay to longitudinally monitor 10 melanoma patients during immune inhibitor blockade treatment. Here, we show that elevated cytokine concentrations predict for higher risk of developing severe immune toxicities in our pilot cohort of patients.

Amplification-Free SARS-CoV-2 Detection Using Nanoyeast-scFv and Ultrasensitive Plasmonic Nanobox-Integrated Nanomixing Microassay.

The implementation of accurate and sensitive molecular detection for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is paramount to effectively control the ongoing coronavirus disease 2019 (COVID-19) pandemic. In this regard, we herein propose the specific and highly sensitive SARS-CoV-2 detection based on nanoyeast single-chain-variable fragment (scFv) and ultrasensitive plasmonic nanobox-integrated nanomixing microassay. Importantly, this designed platform showcases the utility of nanoyeast-scFvs as specific capture reagents targeting the receptor-binding domain (RBD) of the virus and as monoclonal antibody alternatives suitable for cost-effective mass production and frequent testing. By capitalizing on single-particle active nanoboxes as plasmonic nanostructures for surface-enhanced Raman scattering (SERS), the microassay utilizes highly sensitive Raman signals to indicate virus infection. The developed microassay further integrated nanomixing for accelerating molecular collisions. Through the synergistic working of nanoyeast-scFv, plasmonic nanoboxes, and nanomixing, the highly specific and sensitive SARS-CoV-2 detection is achieved as low as 17 virus/µL without any molecular amplification. We successfully demonstrate SARS-CoV-2 detection in saliva samples of simulated patients at clinically relevant viral loads, suggesting the possibility of this platform for accurate and noninvasive patient screening.