A wavelength dependent investigation of the indole photophysics via ionization and fragmentation pump-probe spectroscopies.

A wavelength dependent study investigating the low-lying (1)La and (1)Lb states, both possessing (1)ππ* character, and the (1)πσ* state in the deactivation process of indole is presented here. Relaxation dynamics following excitation at 241, 250, 260, 270, 273, and 282 nm are examined using three gas-phase, pump-probe spectroscopic techniques: (1) hydrogen atom (H-atom) time-resolved kinetic energy release (TR-KER), (2) time-resolved photoelectron spectroscopy (TR-PES), and (3) time-resolved ion yield (TR-IY). Applied in combination, a more complete picture of the indole relaxation dynamics may be gleaned. For instance, TR-PES experiments directly observe all relaxation pathways by probing the evolution of the excited states following photoexcitation; whereas, TR-KER measurements indirectly, yet specifically, probe for (1)πσ*-state activity through the detection of H-atoms eliminated along the indole nitrogen-hydrogen (N-H) stretch coordinate-a possible outcome of (1)πσ*-state relaxation in indole. In addition, mass information obtained via TR-IY monitors fragmentation dynamics that may occur within the neutral electronically excited and/or cationic states. The work herein assesses the onset and importance of the (1)πσ* state at various pump wavelengths by systematically tuning across the ultraviolet absorption spectrum of indole with a particular focus on those pump wavelengths longer than 263 nm, where the involvement of the (1)πσ* state is under current debate. As far as this experimental work is concerned, there does not appear to be any significant involvement by the (1)πσ* state in the indole relaxation processes following excitation at 270, 273, or 282 nm. This investigation also evaluates the primary orbital promotions contributing to the (1)La, (1)Lb, and (1)πσ* transitions based on ionization preferences observed in TR-PES spectra. Relaxation time constants associated with dynamics along these states are also reported for excitation at all of the aforementioned pump wavelengths and are used to pinpoint the origin of the discrepancies found in the literature. In this context, advantages and disadvantages of the three experimental techniques are discussed.

YCharOS open antibody characterisation data: Lessons learned and progress made.

YCharOS is a collaborative initiative aimed at characterising antibodies against the entire human proteome. As of August 2023, they have presented comprehensive knockout characterisation data for 812 antibodies and 78 proteins using techniques such as Western blot, immunoprecipitation, and immunofluorescence. YCharOS consolidates its data into reports (one protein per report) available on Zenodo, a public repository controlled by CERN, to ensure open access. To enhance the visibility of their work, the group is progressively converting their Zenodo reports into F1000 articles, collected on the YCharOS Gateway, and indexed via PubMed. Their data is also accessible through searches on the Antibody Registry. The provided data is a valuable resource for researchers when selecting antibodies for specific applications, although certain limitations should be considered. The data accumulated thus far has illuminated the extent of the problem when poorly performing antibodies are employed in research. While the scientific community was already aware that this was likely a widespread issue, the establishment of a collaborative open science project with industry partners introduces an innovative solution that holds the potential to yield significant returns on investment in the public interest. This potential is substantiated by the number of antibodies that have either been withdrawn or had their recommended usage altered by the vendor. However, despite the discovery of high-performing renewable antibodies for most of the studied proteins, this accounts for a tiny fraction of the human proteome and the commercial antibody market. To realise the full potential of this work, end-users must adjust their antibody procurement and usage practises in line with the provided data. This editorial offers a guide on how individual scientists can utilise the YCharOS data, in addition to sharing the insights gained from the data thus far with the wider scientific community.

Scaling of an antibody validation procedure enables quantification of antibody performance in major research applications.

Antibodies are critical reagents to detect and characterize proteins. It is commonly understood that many commercial antibodies do not recognize their intended targets, but information on the scope of the problem remains largely anecdotal, and as such, feasibility of the goal of at least one potent and specific antibody targeting each protein in a proteome cannot be assessed. Focusing on antibodies for human proteins, we have scaled a standardized characterization approach using parental and knockout cell lines (Laflamme et al., 2019) to assess the performance of 614 commercial antibodies for 65 neuroscience-related proteins. Side-by-side comparisons of all antibodies against each target, obtained from multiple commercial partners, demonstrates that: i) more than 50% of all antibodies failed in one or more tests, ii) yet, ~50-75% of the protein set was covered by at least one high-performing antibody, depending on application, suggesting that coverage of human proteins by commercial antibodies is significant; and iii) recombinant antibodies performed better than monoclonal or polyclonal antibodies. The hundreds of underperforming antibodies identified in this study were found to have been used in a large number of published articles, which should raise alarm. Encouragingly, more than half of the underperforming commercial antibodies were reassessed by the manufacturers, and many had alterations to their recommended usage or were removed from the market. This first such study helps demonstrate the scale of the antibody specificity problem but also suggests an efficient strategy toward achieving coverage of the human proteome; mine the existing commercial antibody repertoire, and use the data to focus new renewable antibody generation efforts.

Scaling of an antibody validation procedure enables quantification of antibody performance in major research applications.

Antibodies are critical reagents to detect and characterize proteins. It is commonly understood that many commercial antibodies do not recognize their intended targets, but information on the scope of the problem remains largely anecdotal, and as such, feasibility of the goal of at least one potent and specific antibody targeting each protein in a proteome cannot be assessed. Focusing on antibodies for human proteins, we have scaled a standardized characterization approach using parental and knockout cell lines (Laflamme et al., 2019) to assess the performance of 614 commercial antibodies for 65 neuroscience-related proteins. Side-by-side comparisons of all antibodies against each target, obtained from multiple commercial partners, have demonstrated that: (i) more than 50% of all antibodies failed in one or more applications, (ii) yet, ~50-75% of the protein set was covered by at least one high-performing antibody, depending on application, suggesting that coverage of human proteins by commercial antibodies is significant; and (iii) recombinant antibodies performed better than monoclonal or polyclonal antibodies. The hundreds of underperforming antibodies identified in this study were found to have been used in a large number of published articles, which should raise alarm. Encouragingly, more than half of the underperforming commercial antibodies were reassessed by the manufacturers, and many had alterations to their recommended usage or were removed from the market. This first study helps demonstrate the scale of the antibody specificity problem but also suggests an efficient strategy toward achieving coverage of the human proteome; mine the existing commercial antibody repertoire, and use the data to focus new renewable antibody generation efforts.

Commercially produced antibodies are essential research tools. Investigators at universities and pharmaceutical companies use them to study human proteins, which carry out all the functions of the cells. Scientists usually buy antibodies from commercial manufacturers who produce more than 6 million antibody products altogether. Yet many commercial antibodies do not work as advertised. They do not recognize their intended protein target or may flag untargeted proteins. Both can skew research results and make it challenging to reproduce scientific studies, which is vital to scientific integrity. Using ineffective commercial antibodies likely wastes $1 billion in research funding each year. Large-scale validation of commercial antibodies by an independent third party could reduce the waste and misinformation associated with using ineffective commercial antibodies. Previous research testing an antibody validation pipeline showed that a commercial antibody widely used in studies to detect a protein involved in amyotrophic lateral sclerosis did not work. Meanwhile, the best-performing commercial antibodies were not used in research. Testing commercial antibodies and making the resulting data available would help scientists identify the best study tools and improve research reliability. Ayoubi et al. collaborated with antibody manufacturers and organizations that produce genetic knock-out cell lines to develop a system validating the effectiveness of commercial antibodies. In the experiments, Ayoubi et al. tested 614 commercial antibodies intended to detect 65 proteins involved in neurologic diseases. An effective antibody was available for about two thirds of the 65 proteins. Yet, hundreds of the antibodies, including many used widely in studies, were ineffective. Manufacturers removed some underperforming antibodies from the market or altered their recommended uses based on these data. Ayoubi et al. shared the resulting data on Zenodo, a publicly available preprint database. The experiments suggest that 20-30% of protein studies use ineffective antibodies, indicating a substantial need for independent assessment of commercial antibodies. Ayoubi et al. demonstrated their side-by-side antibody comparison methods were an effective and efficient way of validating commercial antibodies. Using this approach to test commercial antibodies against all human proteins would cost about $50 million. But it could save much of the $1 billion wasted each year on research involving ineffective antibodies. Independent validation of commercial antibodies could also reduce wasted efforts by scientists using ineffective antibodies and improve the reliability of research results. It would also enable faster, more reliable research that may help scientists understand diseases and develop new therapies to improve patient's lives.

TGFß1 induces resistance of human lung myofibroblasts to cell death via down-regulation of TRPA1 channels.

BACKGROUND AND PURPOSE: TGFß1-mediated myofibroblast activation contributes to pathological fibrosis in many diseases including idiopathic pulmonary fibrosis (IPF), where myofibroblast resistance to oxidant-mediated apoptosis is also evident. We therefore investigated the involvement of redox-sensitive TRPA1 ion channels on human lung myofibroblasts (HLMFs) cell death and TGFß1-mediated pro-fibrotic responses. EXPERIMENTAL APPROACH: The effects of TGFß1 stimulation on TRPA1 expression and cell viability was studied in HLMFs derived from IPF patients and non-fibrotic patients. We also examined a model of TGFß1-dependent fibrogenesis in human lung. We used qRT-PCR, immunofluorescent assays, overexpression with lentiviral vectors and electrophysiological methods. KEY RESULTS: TRPA1 mRNA, protein and ion currents were expressed in HLMFs derived from both non-fibrotic patient controls and IPF patients, and expression was reduced by TGFß1. TRPA1 mRNA was also down-regulated by TGFß1 in a model of lung fibrogenesis in human lung. TRPA1 over-expression or activation induced HLMF apoptosis, and activation of TRPA1 channel activation by H2 O2 induced necrosis. TRPA1 inhibition following TGFß1 down-regulation or pharmacological inhibition, protected HLMFs from both apoptosis and necrosis. Lentiviral vector mediated TRPA1 expression was also found to induce sensitivity to H2 O2 induced cell death in a TRPA1-negative HEK293T cell line. CONCLUSION AND IMPLICATIONS: TGFß1 induces resistance of HLMFs to TRPA1 agonist- and H2 O2 -mediated cell death via down-regulation of TRPA1 channels. Our data suggest that therapeutic strategies which prevent TGFß1-dependent down-regulation of TRPA1 may reduce myofibroblast survival in IPF and therefore improve clinical outcomes.

DP2 antagonism reduces airway smooth muscle mass in asthma by decreasing eosinophilia and myofibroblast recruitment.

Increased airway smooth muscle mass, a feature of airway remodeling in asthma, is the strongest predictor of airflow limitation and contributes to asthma-associated morbidity and mortality. No current drug therapy for asthma is known to affect airway smooth muscle mass. Although there is increasing evidence that prostaglandin D2 type 2 receptor (DP2) is expressed in airway structural and inflammatory cells, few studies have addressed the expression and function of DP2 in airway smooth muscle cells. We report that the DP2 antagonist fevipiprant reduced airway smooth muscle mass in bronchial biopsies from patients with asthma who had participated in a previous randomized placebo-controlled trial. We developed a computational model to capture airway remodeling. Our model predicted that a reduction in airway eosinophilia alone was insufficient to explain the clinically observed decrease in airway smooth muscle mass without a concomitant reduction in the recruitment of airway smooth muscle cells or their precursors to airway smooth muscle bundles that comprise the airway smooth muscle layer. We experimentally confirmed that airway smooth muscle migration could be inhibited in vitro using DP2-specific antagonists in an airway smooth muscle cell culture model. Our analyses suggest that fevipiprant, through antagonism of DP2, reduced airway smooth muscle mass in patients with asthma by decreasing airway eosinophilia in concert with reduced recruitment of myofibroblasts and fibrocytes to the airway smooth muscle bundle. Fevipiprant may thus represent a potential therapy to ameliorate airway remodeling in asthma.