DOI: 10.25338/b8pw6x
title: Flow virometry for water-quality assessment: Protocol optimization for a model virus and automation of data analysis

description: Flow virometry (FVM) can support advanced water treatment and reuse by
 delivering near real-time information about viral water quality. But
 maximizing the potential of FVM in water treatment and reuse applications
 requires protocols to facilitate data validation and interlaboratory
 comparison—as well as approaches to protocol design to extend the suite of
 viruses that FVM can feasibly and efficiently monitor. In the npj Clean
 Water article “Flow virometry for water-quality assessment: Protocol
 optimization for a model virus and automation of data analysis,” we
 address these needs by first optimizing a sample-preparation protocol for
 a model virus (T4 bacteriophage) using a fractional factorial experimental
 design. We then compare manual and algorithmic methods of analyzing
 complex FCM data collected by applying the optimized protocol to (i) a
 clean solution spiked with a variety of biological and non-biological
 viral surrogates [mixed-target experiment], and (ii) tertiary treated
 wastewater effluent spiked with T4 bacteriophage and two sizes of
 fluorescent polystyrene beads [environmental spike experiment]. This
 repository contains the FCM data used to develop the optimized protocol
 and to test the two analytical methods.
description: All data were collected by analyzing a 10-mL volume of the sample
 in question using the 488 nm (blue) solid-state laser, the lowest possible
 instrument flowrate (5 mL/min), and a FITC = 800 threshold on a NovoCyte
 2070V Flow Cytometer coupled with a NovoSampler Pro autosampler (Agilent).
 Green fluorescence (FITC) intensity was collected at 530 ± 30 nm; forward
 and side scatter (FSC and SSC) intensities were collected as well. For the
 optimization experiments, 10 mL of an unstained control was run after each
 sample. The instrument was flushed in between each sample and control by
 running 150 mL of 1x NovoClean solution (Agilent) followed by 150 mL of MQ
 water through the SIP at the highest instrument flow rate (120 mL/min).
 Instrument performance was ensured by performing the instrument’s built-in
 quality control (QC) test at least monthly. The FCM data were exported
 directly to .fcs (the standard format for flow cytometry/virometry data)
 files. All of the raw .fcs files used for the optimization experiments,
 mixed-target experiments, and environmental spike experiments are provided
 in this repository. For the mixed-target and environmental spike
 experiments, these .fcs files were then manually gated and exported to
 .csv files for use in downstream, algorithmically assisted analysis. Each
 of these .csv files is provided in this repository as well.
description: For our analysis, we used the following tools:
 FlowJo<sup>TM</sup> 10 software (Becton Dixon &
 Company) to manually open and analyze the .fcs files, and to convert these
 files to .csv files where needed; Rstudio (version 2021.9.1.372) for
 downstream analysis of results and data obtained using FlowJo; MATLAB®
 software (version R2021a; MathWorks) to perform additional downstream
 analysis; and Excel (version 16.68; Microsoft) to manually inspect the
 .csv files. A list of free and open-source alternative programs that can
 be used to analyze the .fcs files contained in this repository can be
 found at https://floreada.io/flow-cytometry-software. A variety of free and open-source alternative programs (e.g., Google Sheets) exist to analyze the .csv files contained in this repository. For the optimization experiments, subsequent direct analysis of these data (manual gating and calculation of the number, mean fluorescence intensity, and coefficient of variation of all gated particles) was performed using FlowJo<sup>TM</sup> 10 software (Becton Dixon & Company). The FrF2 package in Rstudio (version 2021.9.1.372) was then used to quantify the main and two-way interaction effects of each factor tested in the optimization. Documentation for this package is available at https://www.rdocumentation.org/packages/FrF2/versions/2.1/topics/FrF2-package. For the mixed-target and environmental spike experiments, subsequent direct analysis of these data through manual gating was performed using the same FlowJo software. The FlowJo software was then used to export the gated data to .csv files, FlowJo<sup>TM</sup> 10 software. A log transformation was applied to these data, after which features were standardized by centering and rescaling to standard deviation 1. Rstudio (version 2021.9.1.372) was used to apply the OPTICS implementation available in the dbscan package (Hahsler et al. 2019). MATLAB® software (version R2021a; MathWorks) was then used to inspect reachability plots of the OPTICS-ordered data for manual extraction. Finally, we applied the opticskxi package available in R (Charlton 2019) for automated extraction, with parameters described in the companion article to this dataset.