Terrestrial soils are habitats to an unparalleled abundance and diversity of bacteria and fungi (Delgado-Baquerizo et al., 2016; Fierer and Jackson, 2006; Horner-Devine et al., 2004). The metabolic activities of these microbes drive critical biogeochemical processes with biosphere-level effects (Pold and DeAngelis, 2013; Wieder et al., 2013). However, the opacity and complexity of natural soils present a formidable challenge to the study of soil microbes in their native habitats.

‘Transparent soils’ (TS) are model systems where particles with a similar refractive index (RI) as their saturating liquids allow transmission of light and render a porous, ‘soil-like’ system optically transparent (Iskander, 2010). TS systems have been used for over 25 years in geoengineering and hydrology, where they have helped solve challenging problems in soil physics (Iskander et al., 2015). Despite their importance in that field, however, TS systems have only recently and rarely been used for applications in biology. In part, this is due to soil physicists favoring TS systems that use RI-matching liquids that do not support life, such as silicone oil. In 2005, however, work by Leis et al., 2005 introduced the synthetic fluoropolymer Nafion (Chemours, Wilmington, DE) as a TS that could be RI-matched to water-based solutions that are compatible with culturing microorganisms in situ. Downie et al., 2012; Downie et al., 2014 then demonstrated that plant roots with native-like architectures could be grown and visualized in Nafion-based TS (Downie et al., 2012). Surprisingly, given the novel visualization abilities it provides, the Nafion TS system has only been sparsely utilized for studying biological systems (Downie et al., 2014; Downie et al., 2012; O'Callaghan et al., 2018). This may be due to (a) the high cost of Nafion and (b) the RI of Nafion (RI = 1.35; Leis et al., 2005) not matching water closely enough (RI = 1.333) to allow deep (millimeter to centimeter) imaging. Indeed, Ma and colleagues cited these reasons as their motivation for developing an inexpensive hydrogel-bead-based TS system for root phenotyping (Ma et al., 2019). These hydrogel beads, however, are poorly suited for microbial visualization due to their large size (~500 µm) (Ma et al., 2019), and their susceptibility to degradation by microbes as a carbon source (Rice et al., 1992; Lin et al., 2018).

Despite its limitations for plant root imaging studies, as we show here, Nafion remains a useful and versatile model for soil microbial ecology studies when microcosms utilizing only a few micrograms of TS are used; these chambers only require imaging depths of tens or hundreds of microns (and thus are tolerant of slight RI mismatches) and are inexpensive to build. We further show that cryolite (a naturally-occuring sodium aluminum fluoride crystal) is another promising biocompatible TS substrate with high potential for microbial studies. Cryolite’s RI (=1.339) (Lewis, 2007) renders it effectively entirely transparent in aqueous solutions. Cryolite has previously been utilized to gain insights into the burrowing behaviors of marine invertebrates (Flessa, 1972; Francoeur and Dorgan, 2014; Dorgan, 2018), the swimming behavior of Bacillus subtilis (Zhu et al., 2014), and the spatial patterns of oxygen consumption by a bacterial pseudomonad species (Oates et al., 2005), but its potential for microbial ecology studies remains largely unexplored.

Gaining greater insight into microbial spatial distributions, migration, and growth dynamics – as well as into the physiological states and ecological functions of individual cells and species – is critical to the future of the field (Fike et al., 2008; Berry et al., 2015). In this study, we critically evaluate the capabilities of both Nafion and cryolite as TS substrates for advancing experimental research in soil microbial ecology by generating three-dimensional matrices containing pore spaces analogous to those bacteria inhabit in terrestrial soils (Dal Ferro and Morari, 2015; Deng et al., 2015; Baveye et al., 2018). We show that TS microcosms made of both Nafion and cryolite are amenable to high-resolution, three-dimensional imaging by fluorescence and confocal microscopy, and additionally are compatible with Raman microspectroscopy – a powerful non-destructive method to obtain physiological information about cell states and microbial metabolic activity and nutrient uptake (Huang et al., 2004; Huang et al., 2009; Li et al., 2012; Li et al., 2013; Berry et al., 2015; Kumar B N et al., 2016). Both TS substrates enable the measurement of deuterium uptake as a marker of microbial activity, while cryolite-based TS microcosms further enable the measurement of microbial uptake of isotopically labeled (¹³C) carbon.

We use these tractable, structurally complex TS systems to address an important and experimentally challenging question in soil microbial ecology: how bacteria respond to desiccation and rehydration. Specifically, we ask how metabolically active bacteria are within the TS matrix depending on their proximity to fungal hyphae after a desiccation event. To our knowledge, this is the first study to perform Raman microspectroscopy of cells within a transparent porous matrix, with important potential applications to fundamental problems in soil and sediment microbial ecology. We anticipate that approaches described here will establish these TS systems as novel tools to non-destructively monitor microbial distributions and activity as well as carbon flow through complex, porous, soil-like systems to answer important questions about the ecophysiology of microbes within soils.

By employing stable isotope probing methods, we were able to detect bacterial activity and carbon uptake within TS microcosms, enabling the non-destructive measurement of the metabolic activity of single cells in a spatially resolved manner. This allowed us to gain insights into an ecologically important process: the microbial response to soil drying and rewetting cycles. This work also establishes the suitability of such microcosms to address additional pressing questions in soil microbial ecology.

In this study, we visualized micrometer-sized bacteria by imaging through TS volumes that represent large bacterial habitats (~100 µm). Although previous studies have used light microscopy to image bacteria with single-cell resolution in transparent porous media (Leis et al., 2005; Oates et al., 2005; Drescher et al., 2013), this work further successfully demonstrates the application and combination of light microscopy and Raman microspectroscopy through deep volumes of TS to visualize microbial distributions and measure metabolic states. Achieving Raman spectroscopy in TS is a particularly ambitious goal: even with perfect refractive index matching, surface refraction and surface scattering by TS substrates can contribute background noise and decrease the intensity of the Raman signal (Everall, 2010; Freebody et al., 2010). Despite these challenging conditions, we were able to detect cell-specific Raman spectra from single, micrometer-sized bacteria throughout hydrated TS matrices.

We summarize the properties of both the polymer Nafion and the crystal cryolite for their suitability to soil microbial ecology studies in Table 1. Both substrates are non-toxic to heterotrophic bacteria and fungi, are inert (i.e. not readily decomposed); enable the visualization of fluorescent cells through 100 µm depth; have soil-relevant cation exchange properties (empirically measured for Nafion [Downie et al., 2012]; theoretically inferred for cryolite [see below]); and are compatible with stable isotope probing by Raman microspectroscopy. However, the two TS substrates have important differences. Nafion has the advantage of being commercially available and pure – as opposed to cryolite crystal, which is sporadically available through gem vendors and may include impurities like siderite, fluorite, and quartz (Pauly et al., 1999). It is important to note that synthetically produced cryolite is not recommended as a TS due to the prevalence of sub-micron particles that highly scatter light, the prevalence of opaque aluminum oxides (Flessa, 1972), and an amorphous molecular structure that leads to higher baseline Raman spectra (Tushcel, 2017).

Cryolite has several advantages over Nafion as a TS substrate. It is considerably cheaper than Nafion (tens of cents per gram as opposed to tens of dollars per gram), readily ground into powder of desired particle sizes by mortar and pestle (as opposed to Nafion, which must be cryomilled or bought pre-ground), and requires no pre-treatment before use (unlike Nafion which requires an extensive number of washes to appropriately functionalize). Cryolite also has the advantage of being extremely optically transparent: micron-sized bacteria can be resolved through even 100 µm of hydrated matrix even under brightfield or DIC illumination on a compound microscope (Figure 4, Figure 2—figure supplement 1). This makes cryolite an attractive candidate for soil microbial ecology studies, since bacteria may be visualized even without being fluorescently labeled, obviating the need for genetic modification or staining. Cryolite also has more natural dry-down and wet-up behavior than Nafion (which requires small amounts of surfactants [15% ethylene glycol or 0.1% Tween] to be re-wet after drying; although generally non-toxic [Blank et al., 1987; Man et al., 2017], both of these surfactants can cause cell stress [Hallsworth et al., 2003; Nielsen et al., 2016] and can be potential sources of nutrient contamination [Man et al., 2017]).

An additional consideration for TS materials is their surface charge properties – notably their cation-exchange capacities. After acid washing, the sulfonyl group of Nafion becomes negatively charged with a measured cation exchange capacity of 81 meq per 100 g (Downie et al., 2012). Cryolite particles carry a negative charge when in solutions at a pH greater than 1.5 (Kosmulski, 2009; Lindblad and Duroux, 2017); they are therefore predicted to participate in cation exchange reactions in the pH ranges found in soils (pH 3 to 10; Slessarev et al., 2016). For comparison, the point of zero charge for clays are 2.5 for montmorillonite and 4.6 for kaolinite, both of which are important determinants of the cation-exchange capacities of soils (Kosmulski, 2009). Thus, both of these TS substrates have cation-exchange capabilities consistent with those expected of natural soils.

These surface properties may also be important to the surprising observed difference in B. subtilis 3610 growth habit in Nafion compared to cryolite microcosms (Figure 4, Figure 5, Videos 1–4). Cells were inoculated as single cells at low initial cell densities into TS microcosms. Cell clusters and filaments (indicating microcolony growth) were visible after 48 hr. In liquid MSgg, about 65% of cells grow into filaments (Vlamakis et al., 2008) like the ones visible in Nafion microcosms (Figure 4A, Figure 5A [left], and Videos 1 and 2). The hydrophobic Teflon backbone of Nafion may make it resistant to attachment by B. subtilis; the cells therefore grow not on the Nafion particles but largely within the MSgg liquid phase in the microcosm, and thus resemble filaments grown in liquid MSgg. Intriguingly, cryolite appears to induce cell cluster formation in B. subtilis, even in liquid MSgg. The cells localize to cryolite particle surfaces where they form small clusters, not filaments (Figure 4b, Figure 5a [right], and Videos 3 and 4). This clustering may be due to the innate surface properties of cryolite, which is less hydrophobic than Nafion (Moilanen et al., 2007). It is an interesting question for future work to determine whether these cryolite-associated cell clusters are physiologically equivalent to bacterial microcolonies that have been observed in native soils (Grundmann, 2004; Nunan et al., 2003).

We have demonstrated here, for the first time, that it is possible to acquire Raman spectra from cells through both Nafion and cryolite TS matrices. We chose deuterium and ¹³C as stable isotopes because they both produce clear changes in Raman spectra upon cellular uptake, and because they allow questions about microbial activity and carbon metabolism to be explored. D₂O-treated cells measured through Nafion were clearly distinguishable from H₂O-treated cells using a conservative threshold. Thus, single-cell D₂O uptake measurements can be made using Raman microspectroscopy through Nafion-based TS microcosms. In cryolite-based microcosms, however, variability in the CD area led to a large number (20%) of false positives (H₂O-treated cells misclassified as D₂O-labeled) (Figure 6C). It is therefore impossible to confidently assign a single cell in cryolite as being deuterium labeled. However, at the population level, comparisons of D₂O uptake can be made in cryolite – for example, comparing the CD area of 30 cells exposed to a desiccation and rehydration event versus 30 cells that were not exposed to such an event. This limitation was not observed by Berry et al., 2015, whose studies measured the much stronger Raman signals from dried cells on aluminum slides.

Berry et al., 2015 previously found that an accurate metric for D₂O uptake is the Percent CD, defined as the area of the CD region over the sum of the CD region and the CH region of the cell spectrum. The CH region is the area between 2800 and 3100 cm⁻¹, and represents the carbon-hydrogen bonds in cells, which are depleted in deuterium-labeled cells (Berry et al., 2015). In TS microcosms, the CD peak cannot be normalized to the CH region because the measurements are taken in water-filled pores, which produces a large background signal in the CH region due to the Raman spectrum of water itself. In addition, interference from glass and PDMS is high in this region (Lee et al., 2019). This may contribute to the greater variability in the CD region area when cells are measured in TS matrices than when D₂O-grown cells are measured on aluminum slides (Berry et al., 2015).

That said, even without improvements to the optical setup used to acquire Raman spectra within TS microcosms, we expect that substantial gains could be made in cell spectrum quality through improvements in spectral analysis. In this study, our goal was to determine whether any cell signal could be detected over the background of the TS matrix at all. We did indeed detect the cell signal over the background, and used a very simple method to remove the background signal from the cell spectrum: we simply subtracted the Raman spectrum of a nearby point in x-y space from the acquired cell spectrum. However, more sophisticated techniques for removal of defocused light exist and could be applied to improve the quality of spectra obtained from cells within TS matrices, and therefore increase the amount of information that can be derived from these spectra (Everall, 2010). For example, nearest-neighbor deblurring methods, previously used to increase the signal of the focal Raman spectrum over the background of a different out- of-focus substrate, could be applied to TS systems (Govil et al., 1993). A deconvolution-based removal of background signals based on a model of the contribution of the out-of-focus background region to final cell spectrum may also improve the final results.

Detecting ¹³C uptake through TS matrices by Raman microspectroscopy proved more challenging than detecting deuterium: the signal intensities for the ¹³C-associated Raman peaks are weaker than the CD peak (Huang et al., 2004; Berry et al., 2015; Eichorst et al., 2015). Notably, we could not distinguish single ¹³C-labeled cells from ¹²C-labeled cells in Nafion, which may be due to a Nafion-specific C-O-C bond peak in the same region (Bribes et al., 1991); Nafion has other intrinsic Raman peaks in all of the regions that typically indicate ¹³C uptake into cellular biomass (Figure 7—figure supplement 2, Bribes et al., 1991) since it contains a variety of carbon-based bonds. Cryolite, in contrast, has no carbon bonds, but simply a single repeating bond type arranged in a crystal lattice, resulting in a simple Raman spectrum with a single large peak (Figure S4, Lafuente et al., 2016). This low background allows population-level differences in ¹³C uptake to be detected in cryolite TS microcosms.

We used a binary classifier to categorize cells as either labeled or non-labeled, leading to a tradeoff between sensitivity (lower false-negative rate) and specificity (lower false-positive rate). The cut-off values for classification can be tuned to favor either sensitivity or specificity, depending on the application. For example, Ho and co-workers used a binary classifier to classify methicillin-resistant and methicillin-susceptible Staphylococcus aureus strains based on their Raman spectra (Ho et al., 2019). Because the consequences of a false negative (misdiagnosing a harmful resistant strain as a benign susceptible strain) were more severe than the reverse, the authors tuned the classifier to favor greater sensitivity (a lower false-negative rate). Similarly, in using Raman spectra to classify isotopically labeled and non-labeled organisms, cut-off values should be chosen with the research application and the tradeoff between sensitivity and specificity in mind.

The ability to spatially monitor the distributions and activities of single and populations of cells in soil-like microcosms opens up the possibility of using these TS systems to address long-standing questions in microbial soil ecology. One such question is the role of fungal hyphae in protecting bacterial cells from desiccation and rehydration stress. As soils regularly undergo drying and rewetting events, microorganisms must rapidly adapt to the cellular stress of enormous changes in osmolarity and nutrient availability (Chen and Alexander, 1973; Hallsworth et al., 2003; Barnard et al., 2013; Kakumanu et al., 2013). A previous study using NanoSIMS indicated that B. subtilis cells take up water, carbon, and nitrogen from nearby fungal hyphae in dry, oligotrophic conditions (Worrich et al., 2017). Our Raman microspectroscopy approach is consistent with these results. We found that most B. subtilis cells (60% to 70% in each replicate microcosm) do not show any detectable uptake of D₂O after dessication and rehydration (Figure 8B, right panel) indicating their lack of activity. Berry et al., 2015 were able to detect the CD peak in exponentially growing E. coli cells in as soon as 20 min, which is about half of the cell doubling time (47 min), indicating that incorporation of deuterium into macromolecules is detectable well before cell division. In nutrient-replete liquid shaking cultures, lab strains of E. coli and B. subtilis have comparable growth rates. We roughly estimate that the cells in our experiment, which were incubated for 16 hr with no detectable signal, had a doubling time over twice as long as the incubation time (therefore greater than 32 hr), indicating that they were either growing extremely slowly relative to replete liquid shaking conditions (over 50 times slower), or were dormant, non-viable, or dead.

The high percentage of non-active cells demonstrates how stressful dry-wet cycles can be, even to bacteria such as Bacillus that are considered well-adapted to life in the soil. However, of the cells that showed uptake of D₂O, those attached to M. fragilis hyphae took up more deuterium than those cells far from M. fragilis hyphae (i.e. 3 mm away). Cells near but not on M. fragilis hyphae – that is cells within 20 µm of the hyphae – showed slightly but not significantly higher D₂O uptake than cells far away. Unlike other single-cell resolution stable isotoping methods like NanoSIMS, Raman microspectroscopy in TS microcosms preserves pore structure since it does not require thin sectioning or dehydration of the sample. Thus, this approach allows measurement of cells not only attached to hyphae, but also those attached to nearby, undisturbed particles.

Improvements in microscopic methods, Raman spectrum analysis, and microcosm reproducibility could be made to further extend the utility of TS microcosms (Sharma, 2019). Our method currently has the same limitations as most current microscopy-based methods for investigating environmental microbes: notably, the difficulty of visualizing non-fluorescently tagged, non-genetically tractable microorganisms. Using TS microcosms to study mixed microbial communities therefore presents a significant, but not insurmountable, challenge. While not universally applicable, multiple methods have recently been developed to facilitate the genetic manipulation of wild environmental bacteria (Brophy et al., 2018; Wiles et al., 2018; Xu et al., 2020), which could enable the fluorescent labeling of native bacteria of interest. In the absence of this possibility, morphologically distinct microbes, particularly those of different sizes, could, in principle, be distinguished in TS microcosms. Although, as noted above in Figure 3D, slight distortions in the axial plane may make it more difficult to distinguish rod- from sphere-shaped bacteria at deeper depths, future work could potentially use data obtained from oblong beads of varying sizes to develop normalization algorithms to account for such diffraction issues. Vital dyes such as lectin-binding dyes could be perfused gently into the system to stain cells in situ and thereby increase contrast. If fixation is an option for the experiment in question, FISH or other fixed staining approaches could be used.

There also exists the intriguing possibility of conducing ‘live’ Raman microspectroscopy within the TS microcosms: using Raman spectroscopy not for stable isotope probing (as validated here), but to distinguish and track different microbes non-destructively in situ. There is growing evidence indicating that such strain-specific identifications are possible based solely on the inherent Raman spectra of particular microbes (Manoharan et al., 1990; Harz et al., 2005; Rösch et al., 2005; Harz et al., 2009; Gan et al., 2017). Indeed, for some strains, Raman spectroscopy can even distinguish cells with distinct physiological states within a single strain – for example, sporulating Bacillus cells can be distinguished from vegetative cells by peaks indicating the presence of calcium dipicolinic acid (Ghiamati et al., 1992). Obtaining a better view of these Raman signatures may enable us to utilize Raman microspectroscopy to nondestructively monitor bacterial distributions and spatial organizations within TS microcosms. When the field of microbial ecology as a whole is able to routinely use native cell characteristics (such as these Raman signatures or inherent cellular autofluorescence) to identify ‘wild’ microbes, then this TS microcosm-based method could also be able to be applied towards visualizing native environmental microbes.

In terms of experimental workflow, since the microcosms can be manufactured in batch, the rate-limiting step of utilizing these microcosms (prior to Raman measurements) was the washing steps. The washing and inoculation of microcosms are ideally done on the day of the experiment to maintain sterility, which requires a series of 20 min to 1.5 hr washes (~4 hr of washing total) per microcosm. In addition, since each microcosm requires its own syringe connected to a syringe pump for washing, the number of microcosms that can be prepped simultaneously depends on the number and capacity of syringe pumps available. We had two syringe pumps that handled two syringes each, allowing four microcosms to be washed in parallel. After the washing steps, each microcosm can also be visually checked by microscopy prior to Raman spectroscopy to ensure initial even cell distributions. After inoculation, the rate-limiting step is the manual counting of cells with Raman spectroscopy. A relatively experienced worker can measure about 30 cells with associated background spectra in about 1 to 2 hr.

Further research is needed to definitively assess the reproducibility of TS microcosms. Here, to obtain three replicate microcosms, approximately eight microcosms were initially manufactured. Based on their full particle packing density and strong PDMS-glass seals, six of these were selected for washing; five were retained for inoculation with fungal spores based on their maintenance of high packing density (i.e. minimal loss of particles during washing); four of these were inoculated with bacterial cells based on their well-distributed hyphal growth; and the final three microcosms were used for Raman analysis due to their comparable bacterial cell distributions. For the SIP baseline studies included here (Figures 6 and 7), each boxplot represents the variance within one bacterial culture inoculated into one microcosm. Thus, even within a single biological replicate within a single microcosm, the variation between cells is substantial, although the differences between differently labeled cell populations are detectable and significant. In the D₂O uptake experiment after wet-dry cycling (Figure 8), each replicate represents a single biological culture within a different microcosm, and there are three such replicates in total. The same trends were not observed in each microcosm; as discussed above, ‘replicate’ was itself a significant source of variation. Similar heterogeneity and biological variability have been noted even in other, simpler imaging microcosms than those described here. Deng and co-workers, for example, used nearly identical replicate PDMS-based microfluidic devices that mimic the pore properties of soils, and monitored drying of these microcosms under carefully controlled humidity and temperature conditions (Deng et al., 2015). Even so, variation between their microcosms was considerable, although major trends were still detected.

Thus, although our transparent soil microcosms are considerably simpler and less heterogenous than true soils -- being composed of a single particle type, known particle size distributions, no biological or organic matter at the time of inoculation, and possessing geometric constraints -- there remain several sources of heterogeneity between microcosms. The major cause is particle packing; differences in particle density leads to different rates of liquid flow through the microcosms as well as different distributions of cells within the particle matrix. Careful manufacturing technique (filling PDMS chambers as fully as possible with particles before sealing, discarding microcosms that are under- or over-packed) can help mitigate this problem, as well as the use of narrow particle size distributions, and using overall smaller particle sizes (less than 40 μm). In addition to these efforts, running multiple replicate experiments remains important for increasing confidence in findings and the sensitivity of assays. Alternatively, if the heterogeneity cannot be constrained, it can be measured. An entire microcosm can be imaged in 3D by confocal microscopy prior to or after inoculation in order to extract pore size volumes and distributions (for example, see do Nascimento et al., 2019). Smaller microcosms and coarser-resolution imaging would enable more rapid imaging of the full volume of the microcosm for this purpose.

In conclusion, the TS model microcosms we describe here – in which the locations, morphologies, growth dynamics, movement, and metabolic states of microbes can be non-destructively resolved – open up the possibility of directly testing many outstanding questions in soil microbial ecology. These include investigations into previously occluded processes such as predation and lysis dynamics, microbial migration patterns, conjugation and transduction networks, and interspecies interactions. The inert nature of the TS substrates described here enables the direct examination of the effects of controlled amounts of nutrients and carbon on soil microbiota. Moreover, extensions of these described TS microcosms with fluorescent in situ hybridization (FISH, to identify microbes and their locations) or fluorescent transcriptional reporter strains (to track bacterial gene expression in native soil-like environments) will further expand the impact of these systems for the study of soil microbial ecology and ecophysiology.

All data generated or analyzed during this study are included in the manuscript and supporting files, and source files have been deposited at Dryad.

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Author details

1. Kriti Sharma

   Department of Biology, University of North Carolina, Chapel Hill, United States

   Present address

   Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing

   Competing interests

   No competing interests declared

2. Márton Palatinszky

   Department of Microbiology and Ecosystem Science, Centre for Microbiology and Environmental Systems Science, University of Vienna, Vienna, Austria

   Contribution

   Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

3. Georgi Nikolov

   Department of Microbiology and Ecosystem Science, Centre for Microbiology and Environmental Systems Science, University of Vienna, Vienna, Austria

   Contribution

   Formal analysis, Validation, Investigation, Writing - review and editing

   Competing interests

   No competing interests declared

4. David Berry

   Department of Microbiology and Ecosystem Science, Centre for Microbiology and Environmental Systems Science, University of Vienna, Vienna, Austria

   Contribution

   Conceptualization, Resources, Supervision, Funding acquisition, Validation, Visualization, Methodology, Project administration, Writing - review and editing

   Competing interests

   No competing interests declared

5. Elizabeth A Shank

   1. Department of Biology, University of North Carolina, Chapel Hill, United States
   2. Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, United States
   3. Program in Systems Biology, University of Massachusetts Medical School, Worcester, United States

   Contribution

   Conceptualization, Resources, Supervision, Funding acquisition, Visualization, Methodology, Project administration, Writing - review and editing

   For correspondence

   Elizabeth.Shank@umassmed.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-4804-1966

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