The purpose of this document is to define minimal standards for a flow cytometry shared resource laboratory (SRL) and provide guidance for best practices in several important areas. This effort is driven by the desire of International Society for the Advancement of Cytometry (ISAC) members in SRLs to define and maintain standards of excellence in flow cytometry, and act as a repository for key elements of this information (e.g. example SOPs/training material, etc.). These best practices are not intended to define specifically how to implement these recommendations, but rather to establish minimal goals for an SRL to address in order to achieve excellence. It is hoped that once these best practices are established and implemented they will serve as a template from which similar practices can be defined for other types of SRLs. Identification of the need for best practices first occurred through discussions at the CYTO 2013 SRL Forum, with the most important areas for which best practices should be defined identified through several surveys and SRL track workshops as part of CYTO 2014. © 2016 International Society for Advancement of Cytometry.

Studies of pulmonary inflammation require unique considerations due to the complex structure and composition of the lungs. The lungs have multiple compartments and diverse immune cell populations, with inherently high autofluorescence, and are involved in the host response to pulmonary pathogens. We describe a protocol that accounts for these factors through a novel combination of methodologies - in vivo compartmental analysis and spectral flow cytometry with a broad panel of antibodies. In vivo compartmental analysis enables the precise localization of immune cells within the marginated vasculature, lung interstitium, non-lavageable airways, and lavageable airways of the lungs, as well as the pulmonary lymph nodes. Spectral flow cytometry with a broad panel of antibodies supports an unbiased exploratory approach to investigating diverse immune cell populations during pulmonary inflammation. Most importantly, spectral flow utilizes cellular autofluorescence to aid in the resolution and identification of immune cell populations. This methodology enables the acquisition of high-quality data compatible with informed gating and dimensionality reduction algorithms. Additionally, our protocol emphasizes considerations for compartmentalization of the inflammatory response, spectral flow panel design, and autofluorescence spectra analysis. These methodologies are critical for increasing the rigor of pulmonary research. We apply this protocol for the precise characterization and localization of leukocytes in the pulmonary host response to influenza A virus in C57BL/6J mice. In particular, we demonstrate that this protocol improves the quantification and localization of alveolar macrophages within the airways. The methodology is modifiable and expandable to allow for further characterization of leukocyte populations of special interest.

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FLOW cytometry SRLs are tasked with a wide array of responsibilities and providing technical knowledge to users to ensure high-quality data is an essential function. It is critical to have standard operating procedures (SOP's) to protect the workstations generating the data and a formal system to manage and back up the data. When writing and implementing SOP's, there are multiple considerations to take into account. The possibility of data corruption and accidental deletion of data is at the core of the concerns and usually serves as a starting point of the thought process for making these preparations. However, there are other circumstances to consider in data management. Natural disasters and unforeseen conditions that arise, such as the current pandemic, pose a threat to data management, and considerations for these events is crucial when making a data management plan. There are four interconnected stages to managing an emergency: mitigation, preparedness, response, and recovery; lessons learned through one emergency may help plan and respond in the future (1). Emergency planning is essential to meet the challenges introduced by disaster situations, which can physically destroy data. Evaluating what situations could impact data integrity and implementing practices to mitigate them will ensure that the SRL is prepared and can respond in an emergency or, better yet, eliminate a potential disaster from happening. Mitigation efforts aim to limit an emergency's effect while the response and recovery aid in restoring what was affected or lost and provide an opportunity for improvement. The loss due to floods, fire, or other natural disasters, requires a system that keeps data backed up off-site. SRLs in regions prone to natural disasters have already experienced these challenges; Tulane university faced the difficult reality of the need to backup essential data off-site in the wake of Hurricane Katrina (2). Lessons learned from having locally stored data lost due to widespread damage to buildings have led to implementing systems for keeping data off-site out of the same geographical area to withstand a large-scale disaster. A comprehensive data management plan (Table 1) will prepare for potential threats to the hardware systems where data are collected and stored and respond by implementing practices that safeguard instrument workstations from data loss or corruption, including antiviral and malware software, restricting access to the Internet, and limiting external device connections. Other important considerations revolve around managing information related to raw data files that give data relevance and context, which we will discuss later. Research laboratories across the globe experienced the pandemic's impact. Information obtained through the ISAC SRL COVID-19 survey shows that many institutions began operating with new social distancing rules that included limited contact with others, staggered nonoverlapping work schedules, and working from home when possible (3). SRLs that were shutdown or had limited onsite...