Comprehensive analysis of spinal cord inflammatory factors in HIV Tat-induced neuropathy in mice

Abstract

Despite advancements in HIV treatment, HIV neuropathy, caused by nerve damage following HIV infection, continues to be a major cause of morbidity. Inflammatory responses both in the central and peripheral nervous systems have been implicated as contributing mechanisms, but the role of the HIV protein Trans-Activator of Transcription (Tat) in HIV neuropathy is not well understood. In this study, we report the development of neuropathy-like behavioral changes in doxycycline-inducible HIV Tat transgenic (iTat) mice using comprehensive behavioral assessments. These changes include increased hind paw mechanical sensory sensitivities in both sexes, and increased cold sensitivity and reduced hind paw grip strength predominantly in females. Hind paw skin intra-epidermal nerve fiber (IENF) density showed a small but significant transient increase in the density of CGRP+ fibers at day 21 post-Tat induction in both sexes, while the recovery was faster in females. As Tat is induced primarily in the central nervous system in iTat mice, we therefore focused on elucidating central mechanisms by performing inflammation-targeted RNA profiling in lumbar spinal cord via NanoString assay followed by bioinformatic analysis to identify signaling pathways that may be responsible for the observed symptomatic changes. Three key signaling pathways - apoptosis, inflammation mediated by chemokine and cytokine, and Toll-like receptor signaling pathways - were identified. Subsequent qRT-PCR assays confirmed Tat-induced changes of selected genes. Altogether, we demonstrated that Tat induction is associated with sex-dependent neuropathy-like changes. The concurrent changes in selected inflammation-related signaling pathways within lumbar spinal cord shed light on potential underlying central mechanisms.

Introduction

The global health burden of HIV remains astounding with a steady increase in prevalence despite increased prevention and treatments options; by the end of 2023, 39.9 million people were living with HIV and 630,000 people died due to HIV-related illness (Tian et al., 2023, WHO, 2024). HIV is of particular clinical concern as it can cause a chronic infection that lasts for years and is accompanied by various complications (Swinkels et al., 2024). One of the common disabling complications is HIV-associated neuropathy (Jazebi et al., 2021). In fact, HIV associated distal symmetric polyneuropathy, one type of HIV neuropathy that affects both sensory and motor nerves, is considered one of the most common neurologic complications of HIV (Schütz and Robinson-Papp, 2013, Julian et al., 2021). Due to increased life expectancy among patients with HIV, HIV neuropathy is estimated to be present in 30–60% of individuals infected with HIV, although the prevalence varies with many factors such as local and regional transmission rates of HIV and access to antiretroviral therapy (Jazebi et al., 2021). Jazebi’s review article also identified two studies that reported sex being a potential factor affecting HIV neuropathy development. One study reported female sex as a risk factor for HIV neuropathy in anti-retroviral therapy-exposed patients (Chen et al., 2013). The other study reported female patients with HIV neuropathy could respond better to capsaicin topical treatment, however, this was not conclusive as most participants were male (Katz et al., 2015).

HIV neuropathy can affect nerves throughout the body including peripheral sensory and motor nerves, cranial nerves, and autonomic nerves (JohnsHopkinsMedicine, 2025). HIV peripheral polyneuropathy commonly starts from lower limbs and progresses in a stocking-glove distribution pattern (Schütz and Robinson-Papp, 2013), and symptoms of HIV neuropathy can include numbness, paresthesia, pain, weakness and loss of the deep tendon reflexes (Hao, 2013). The pain from HIV neuropathy is often difficult to manage, as many conventional drugs for neuropathic pain are not effective (Hao, 2013). The cause for HIV-neuropathy is not fully understood. Besides well-known antiretroviral drug-caused neurotoxicity, HIV virus and its products induce symptomatic neurotoxicity that persists despite improved antiretroviral regimens (Jazebi et al., 2021, Schütz and Robinson-Papp, 2013). The involvement of pro-inflammatory cytokines and chemokines, both centrally and peripherally, are implicated in the underlying mechanisms of the development of neurotoxicity and the subsequent HIV neuropathy (Hao, 2013, Jazebi et al., 2021, Schütz and Robinson-Papp, 2013).

One HIV protein thought to strongly contribute to HIV neuropathy is gp120, a viral surface protein that assists HIV in entering host cells. Gp120 has been shown to activate microglia and astrocytes, leading to the release of pro-inflammatory cytokines, neuronal cell death and axonal degeneration (Jazebi et al., 2021). Clinically, gp120 expression has been shown to be increased in patients with HIV neuropathy (Jazebi et al., 2021). Several animal models demonstrated the effects of gp120 in inducing neuropathy-like, particularly pain-like, behaviors, which are often associated with inflammatory responses within the peripheral nerve, dorsal root ganglion (DRG), or spinal cord (Wallace et al., 2007b, Yuan et al., 2014, Zheng et al., 2011, Herzberg and Sagen, 2001, Ledeboer et al., 2005, Milligan et al., 2000, Minami et al., 2003). Recently, another HIV protein, Trans-Activator of Transcription (Tat), a key protein in initiating HIV transcription (Bagashev and Sawaya, 2013), has been explored for its potential role in HIV neuropathy. Tat has been shown to cause neuronal degeneration in vivo and direct neuronal toxicity in vitro (Silvers et al., 2007, Langford et al., 2018, Chi et al., 2011). Clinically, Tat protein has been found in the brains of patients with HIV-associated brain pathology (Silvers et al., 2007). While Tat is secreted by cells infected with HIV, it can also be taken up by other cells; therefore, Tat can affect both infected and non-infected cells (Silvers et al., 2007, Bagashev and Sawaya, 2013). These neurotoxic effects of Tat have been shown to be mediated through Tat’s binding to low density lipoprotein receptor and N-methyl-D-aspartate (NMDA) receptors, which could result in neuronal excitotoxicity, production of proinflammatory cytokines and inflammation, and apoptosis (Kim et al., 2003, Bagashev and Sawaya, 2013, Marks et al., 2016). Using doxycycline-inducible Tat transgenic mice (iTat) models (the He and Nath models) (Bruce-Keller et al., 2008, Kim et al., 2003), researchers have reported selected Tat-associated changes that were consistent with HIV neuropathy (Han et al., 2021, Wodarski et al., 2018, Bagdas et al., 2020, Toma et al., 2022). The iTat models are particularly relevant for investigating the role of Tat in HIV neuropathy as Tat is primarily induced from glial fibrillary acidic protein (GFAP)-expressing astrocytes within the central nervous system (CNS) of these mice, and recent studies have identified astrocytes as HIV reservoirs in addition to microglia (Donoso et al., 2022). Further, astrocytes have been shown to be critical players in pathogenesis of HIV neuropathy both in human disease and in gp120-mediated HIV neuropathy (Zheng et al., 2011, Milligan et al., 2000, Tang, 2022, Shi et al., 2012). In our current study, we further demonstrated neuropathy-like changes through comprehensive behavioral testing, immunohistochemistry (IHC), and nerve conduction studies in the He iTat mouse model, with identification of potential novel contribution of Tat in HIV neuropathy. Ample studies have demonstrated the contribution of neuroinflammation at the spinal cord level to central sensitization and enhanced pain processing (Matsuda et al., 2019, Ji et al., 2018, Vergne-Salle and Bertin, 2021). Since Tat is primarily expressed by GFAP-expressing astrocytes within the CNS, we further explored the spinal cord-mediated mechanisms. We conducted lumbar spinal cord RNA expression profiling and subsequent bioinformatic analysis to identify potential inflammation-related signaling pathways and related factors contributing to Tat-associated HIV neuropathy.

Experimental Procedures

Animals

Adult (7–10 weeks old) wild type (WT) control C57BL/6J mice were purchased from Jackson Laboratories (Bar Harbor, ME), which were used for experiments after being habituated in the institutional facility for at least one week. The doxycycline inducible HIV-1 Tat transgenic mice (iTat) on a C57BL/6J background were obtained from Dr. Johnny He (formerly at the University of North Texas Health Science Center (UNTHSC) at Fort Worth, TX) and were maintained in the University of New England (UNE) Animal Facility. HIV Tat1–86 (which encodes the first and second exons of the Tat protein from HIV-1 HXB2) expression was regulated by the astrocyte-specific murine GFAP promoter that is inducible by doxycycline treatment (Kim et al., 2003). The genotype of iTat mice were periodically checked via PCR as described previously (Kim et al., 2003). Adult iTat mice (2–4 months) with body weights equivalent to WT mice were used in all experiments. All mice were housed at the UNE Animal Facility with a 12-hour light and 12-hour dark photoperiod. Water and food were provided for the animals ad libitum. For Tat induction, Doxycycline hyclate (DOX, Sigma-Aldrich, D9891–5G, St. Louis, MO) at 100 mg/kg was intraperitoneally (i.p.) injected daily for 7, 14, or 21 days at a volume of 250 μl/25 g mouse body weight. This particular dose of DOX has been used previously and the induction of Tat at the protein levels was demonstrated (Carey et al., 2012, Zou et al., 2007). After initial time-response experiments, a 14-day injection regimen was selected and used in all subsequent experiments (Cao, 2019). pH-matched phosphate-buffered saline (PBS) (pH=3) was used as a negative control. In selected experiments, WT mice were injected with DOX to assess potential effects from DOX alone. To assess potential sex differences, we included both males and female animals (~50:50) in all experiments. The specific sample size (n) and animal number per sex for each experiment are listed within the correspondent figure legends. For all experiments, at the end point, animals were euthanized via CO₂ following the guideline published by the American Veterinary Medical Association (AVMA) (TheAVMAPanelonEuthanasia, 2020). A compressed CO₂ gas cylinder was used as the source of CO₂ and 100% CO₂ was introduced into the chamber with animals for euthanasia at a fill rate of ~30–70% displacement of the chamber volume per minute. All animal procedures were approved by the UNE’s Institutional Animal Care and Use Committee (IACUC) and were consistent with federal regulations and guidelines.

Behavioral Tests

To assess behavioral changes following Tat induction, a series of behavioral tests were performed before Tat induction (baseline) and repeatedly at indicated days (as described in each experiment in the result section) up to day 35. Tests were performed in the following order with at least 30–60 min intervals between tests to avoid potential influential effects of early tests on subsequent tests: Grip strength test, mechanical sensitivity test, Hargreaves test, and then cold plantar test. The person performing the behavioral tests was blinded to the experimental groups. Once all behavioral tests were completed at day 35 post the initiation of DOX or PBS injections, all animals were euthanized. To avoid potential influence on biochemical assays tests, cohorts used for behavioral assessment were not used for tissue sample collections.

Mechanical sensitivity test

Mechanical sensitivity was measured as the direct pressure stimulus required to elicit foot-withdrawal in non-restrained conditions with von Frey filaments (Stoelting, Wood Dale, IL) using the up-down method as previously described (Cao et al., 2012, Chaplan et al., 1994). The 50% threshold force needed for paw withdrawal was calculated and used to represent mechanical sensitivity.

Hargreaves test

Heat sensitivity was assayed under non-restrained conditions using the Hargreaves test as previously published (Cao and Malon, 2018) using an IITC Plantar Analgesia Meter (IITC Life Science, Woodland Hills, CA). Specifically, a 24v halogen lamp was focused through a convex lens onto a glass surface under the hind paw and the animal’s withdrawal latency was recorded, with a cut-off time of 30 sec and at least 10 min intervals between tests. The average paw withdrawal latencies from three separate tests were calculated to represent animals’ heat sensitivity.

Cold plantar test

Cold sensitivity was measured using the cold plantar test, which was conducted as previously described (Brenner et al., 2012). Briefly, mice were placed on a 1/4” glass surface and powdered dry ice was packed into a modified 3-ml syringe up to the 2.5–3ml mark on the syringe. The dry-ice exposed end of the syringe was held tightly against the glass surface under the hind paw and the animal’s withdrawal latency was recorded, with a cut-off time of 20 sec and at least 15 min intervals between tests. The average paw withdrawal latencies from three separate tests were calculated to represent animals’ cold sensitivity.

Grip strength test

Hind paw motor function was evaluated via the grip strength test using a Grip Strength Meter (Columbus Instruments, Columbus, OH) following a published method (Bobinski et al., 2011). During testing, each mouse was gently restrained and allowed to grasp the pull bar assembly (a metal bar) with each hind paw. The experimenter then gently but quickly pulled the animal in a rostrocaudal direction until the grip was broken. The peak amount of force the mouse applied in grasping the bar during the process was recorded. For each paw, three repeated trials with at least a one-minute interval between tests were conducted and the average force was calculated and used to represent the paw’s grip strength.

For all tests, both left and right hind paws were tested and the results were averaged to represent the response for each animal. For Hargreaves test, cold plantar test, and grip strength test, due to the high variation between animals, percent changes from baseline at each indicated times were used to represent each animal’s test results. The individual performing the tests was blinded to animal groups during testing.

Nerve Conduction Studies

To assess potential Tat-induced neuropathy-like physiological changes, a nerve conduction study (NCS) along sciatic nerve was performed before Tat induction and on days 3, 7, 14, 21, 28, and 35 following a modified protocol (Osuchowski et al., 2009). The mice were anesthetized with isoflurane (4% in oxygen for induction, 2–3% in oxygen for maintenance), then placed prone on a heating pad (maintained at ~30°C) and restrained using lab tape with hindlimbs extended at the knees and abducted at the hips. The fur on the lower back and legs of the animals were shaved using an electric razor. Solid filament stainless steel (acupuncture) needles of 180 μm diameter were placed sub-dermally for stimulating (1-cm in length) and recording (0.5-cm in length). The anode was placed on the left side just lateral to the midline, with the tip inserted 1 mm caudal to the tail-base and advanced parallel to the spine, and the cathode placed ~3 mm lateral and parallel to the anode. The recording electrode was inserted in the left hind paw. The reference electrode was placed close to the halfway point of the tail. A sticky electrode was used as a ground on the low back. The placement of all electrodes is illustrated in Figure 1. Electric recording was performed via an UltraPro S100F instrument (Natus Neurology Incorporated, Middleton, WI). Each animal was stimulated with incremental impulse intensity until a maximal and artifact-free compound muscle action potential (CMAP) was evoked, and 10 further stimulations were recorded at that stimulation intensity. The amplitude, duration, and latency of the maximal CMAP were obtained as the average of 5 out of the 10 stimulations (usually the 1^st, 3^rd, 5^th, 7^th, and 9^th stimulations) delivered. Note that animals used for nerve conduction studies were different from those used for the comprehensive behavioral tests, and were not used for sample collection or subsequent biochemical assays to avoid any potential influence of repeated nerve conduction studies on any other assays.

Figure 1. Graphic illustration of electrode placement during nerve conduction studies.

The cartoon image shows the lower back, left hind limb, and tail of a mouse that is placed in a prone position. The mouse head (not shown) is towards the top of the image. All electrodes used are marked on the image. Note that recording was performed along the left sciatic nerve, however the sciatic nerve was not exposed during recording.

Immunohistochemistry (IHC)

Hind paw skin was collected from adult iTat mice i.p. injected daily with DOX or PBS injections as described in “Animal” section at days 0 (naïve), 3, 7, 14, 21, 28, and 35 following Tat induction (5–7/sex/time point; separate mice were used at each time point). Post euthanasia via CO₂, a roughly 5 mm² square of glabrous skin encompassing the most proximal footpad and the metatarsal region was isolated from the left and right hind paws and fixed in 4% paraformaldehyde/PBS overnight at 4°C, followed by incubation in 30% sucrose containing 0.01% sodium azide for 48 hrs at 4°C. Tissues were freeze-embedded in O.C.T. Tek II Cryo-compound (VWR 25608–930, Radnor, PA) and stored at −80°C until sectioning. With a cryostat (Leica Biosystems, Deer Park, IL), 14 mm sagittal epidermal sections including the proximal footpad were collected and mounted on Superfrost PLUS microscope slides (VWR 48311–703). Tissue was permeabilized and blocked in 0.4% Triton X-100 (Sigma Aldrich T9284, St. Louis, MO)/PBS with 5% Normal Donkey Serum (Jackson ImmunoResearch 017–000-121, West Grove, PA), followed by staining with primary antibodies against PGP9.5 (pan-neuronal marker, 1:2000, Proteintech 14730–1-AP, RRID:AB_2210497, Rosemont, IL) and calcitonin gene related peptide (CGRP; representing peptidergic nerve fibers, 1:1000, Bio-Rad 1720–9007, RRID:AB_2290729, Hercules, CA) at 4°C overnight, and secondary antibodies goat anti-rabbit Cy3 (Jackson Immunoresearch 111–165-144, RRID:AB_2338006) at 1:1000 and donkey anti-goat Alexa Fluor 488 (Jackson Immunoresearch 705–545-147, RRID:AB_2336933) at 1:1000. Fluoromount-G (Electron Microscopy Sciences 17984–25, Hatfield, PA) with DAPI was added immediately prior to coverslipping and slides were stored in the dark at 4 °C until imaging.

Fluorescent microscopy was conducted with a Keyence BZ-X710 inverted widefield digital microscope with a 20x plan apo objective lens with 0.7 numerical aperture (Keyence Corporation of America, Itasca, IL) using pre-set channels for blue, green, and red wavelengths, using exposure settings appropriate to individual sections. Images were analyzed using ImageJ (Schneider et al., 2012) to determine intraepidermal nerve fiber (IENF) density as a function of number of nerve terminals identified in the epidermal region per unit length of epidermis (mm) (individually measured using ImageJ) for both the red channel (all neurons) as well as the green channel (peptidergic neurons). The contrast and brightness settings of images were adjusted in ImageJ as needed to ensure an accurate identification and counting of any nerve terminals as the nerve terminals are often curving through the epidermis layer and different parts of a given nerve terminal are seen at different focal plans. Between 2–5 images per section and 2–4 sections per sample were analyzed, and averages from each section were averaged together for each side before averaging the left and right paw densities to generate a single value for each animal, with a total of >2,500 individual images contributing to this analysis. Images were renamed and reordered in a random manner to achieve blinded image analysis.

The same method was used to prepare lumbar spinal cord tissues (animals from Day 14 DOX and PBS groups) for IHC with the respective Rat anti-GFAP (1:1500, Invitrogen 13–0300, RRID: AB_2532994, Carlsbad, CA) and Donkey anti-Rat Alexa Fluor 488 (1:1000, Jackson Immunoresearch 712–545-153, RRID: AB_2340684). The same Keyence BZ-X710 inverted widefield digital microscope was used and all images were taken at 20x from 2–4 sections of the same tissue. ImageJ was used to analyze the images to obtain integrated density.

RNA isolation, NanoString Analysis, and Bioinformatic Analysis

At days 0 (naïve), 3, 7, 14, 21, 28, and 35 following Tat induction, lumbar spinal cord from adult iTat mice (3 males and 3 females per time point; separate mice were used at each time point) were collected post euthanasia via CO₂ and stored immediately at −80°C until RNA extraction. RNA was isolated from the lumbar spinal cord using the RNeasy Lipid Tissue Kit (Qiagen, Waltham, MA) following the manufacturer’s instructions. Aliquots of RNA samples were sent to the Dartmouth Genomics and Molecular Biology Core for NanoString gene expression profiling with the mouse inflammation panel (LBL-10402–01) using an nCounter analysis system (NanoString Technologies Inc., Seattle, WA). Raw NanoString data was processed by the Dartmouth Biostatistics and Bioinformatics core with the accompanied nSolver software (RRID:SCR_021712). Gene expression values were normalized by invariant set normalization using internal reference genes included in the nCounter mouse inflammation panel (LBL-10402–01).

For clustering co-regulated genes, normalized mean gene expression values were then inputted into the Short Time-Series Expression Miner Program (STEM, RRID:SCR_005016, V1.8.0_311) (Fan et al., 2021, Ernst and Bar-Joseph, 2006). STEM is a java program that allows the grouping, comparing, and visualization of gene expression data. Using the default parameters of STEM with 45 maximum profiles, significant clusters of co-regulated genes that experienced changes in expression were identified. Genes from each significant cluster were then input into PANTHER software (RRID:SCR_004869) using the PANTHER Gene Ontology-Pathway Analysis to visualize involved signaling pathways (Mi et al., 2019). This was done to elucidate pathways within the significant gene clusters that may contribute to Tat-mediated HIV neuropathy.

To verify expression of selected genes associated with selected identified pathways at the RNA levels using qRT-PCR, lumbar spinal cord from DOX or PBS treated adult iTat mice were collected at days 0 (naïve), 3, 7, 14, 21, 28, and 35 following Tat induction (3 males and 3 females per time point per treatment and total of 3 females and 5 males were used at baseline to ensure sufficient number of mice used for percentage change calculations; separate mice were used at each time point). RNA isolation was performed as described above. To synthesize cDNA, RNA (500 ng) was reverse transcribed to 20 μl of complimentary DNA using Quanta qScript Supermix (Quanta Bio, Beverly, MA). qRT-PCR with synthesized cDNA was performed as previously described (Canonico et al., 2023). Briefly, cDNA was amplified with the primer sets (Table 1) and with the Quanta PerfeCTa^™ SYBR Green FastMix ROX (Quanta Bio, Beverly, MA) using an Applied Biosystems StepOnePlus Real-Time PCR thermocycler (Applied Biosystems, Forest City, CA). GAPDH was used as an internal control and delta-CT was used to calculate the relative expression of each gene. To reduce interexperimental variations, percentage changes from naïve group were further calculated within each experimental cohort. All primers were synthesized by Integrated DNA Technologies (Coralville, IA) and are listed in Table 1 along with the respective PCR protocol.

Table 1:

Primers and Run methods for PCR

Target Gene	Forward Primer/Primer 1	Reverse Primer/Primer 2	Run Method
CCL5a	AGCTGCCCTCACCATCATC	CTCTGGGTTGGCACACACTT	• 95°C for 15 min • 50 cycles of  o 95°C for 15 secs  o 60°C for 1 min
IL-6a	CAGAGGATACCACTACCAACAG	TCTCATTTCCACCACGATTTCCC
IFN-ga	GCCATCAGCAACAACATAAGC	CAGCAGCGACTCCTTTTCC
Alox12b	GCTCCAATTCCATTTGCTGAAC	GCTTCGCGTGTTAATTTCCATAG	• 95°C for 30 secs • 40 cycles of  o 95°C for 3 secs  o 60°C for 30 secs with fast ramp speed
Atf2b	GCCTTTAAAGTGCGATTCAGC	CTTCCCAAGTTGCCATCTAGT
Bcl2L1b	ATTCAGCACGAGCAGTCAG	ATTCAGCACGAGCAGTCAG
C3ar1b	GATTCCATCTCAGTGTGCTTG	GATTCCATCTCAGTGTGCTTG
CCL11b	CTTCTATTCCTGCTGCTCACG	CTTCTATTCCTGCTGCTCACG
CCL20b	CCAGCACTGAGTACATCAACT	CCAGCACTGAGTACATCAACT
CCL22b	ACTACATCCGTCACCCTCTG	ACTACATCCGTCACCCTCTG
Creb1b	AGCACTTCCTACACAGCCT	AGCACTTCCTACACAGCCT
Cxcr4b	CGTTTGGTGCTCCGGTAA	CGTTTGGTGCTCCGGTAA
Elk1b	GCAAGAACAAGACCAACATGA	GCAAGAACAAGACCAACATGA
GAPDHb	GTGGAGTCATACTGGAACATGTAG	AATGGTGAAGGTCGGTGTG
GFAPb	GCATCTCCACAGTCTTTACCA	AACCGCATCACCATTCCTG
Gnaqb	CCTTCCTATCTGCCTACACAAC	CCTTCCTATCTGCCTACACAAC
Irf3b	AGCCGTGTTCGACCTCA	AGCCGTGTTCGACCTCA
Junb	GCATGGACCTAACATTCGATCT	GCATGGACCTAACATTCGATCT
LTAb	CTCAGAAGCACTTGACCCAT	CTCAGAAGCACTTGACCCAT
Mapkb	CTACACCAACCTCTCGTACATC	CTACACCAACCTCTCGTACATC
Mapk3b	TCCAGATCTTGCTGCGATTC	TCCAGATCTTGCTGCGATTC
Mapk8b	GGAGGAACGAACTAAGAATGGAG	GGAGGAACGAACTAAGAATGGAG
Map3k1b	ACCATCCAGAAGTTTGTGTCA	ACCATCCAGAAGTTTGTGTCA
Map3k7b	CGTCTTCTGCCAGTGAGATG	CGTCTTCTGCCAGTGAGATG
Map2k4b	GGATGTAGTAATGCGGAGTAGTG	GGATGTAGTAATGCGGAGTAGTG
Myd88b	GTGAGGATATACTGAAGGAGCTG	GTGAGGATATACTGAAGGAGCTG
Nfatc3b	TTCTTTCAGTTCCTTCACCCTT	TTCTTTCAGTTCCTTCACCCTT
Prkcab	TGTACCACATTCAGCAAGTCG	TGTACCACATTCAGCAAGTCG
Prkcbb	CGTATCCCAAGTCCATGTCC	CGTATCCCAAGTCCATGTCC
Relab	GAGTTCCAGTACTTGCCAGAC	GAGTTCCAGTACTTGCCAGAC
Rhoab	GCTCATAGTCTTCAGCAAGGAC	GCTCATAGTCTTCAGCAAGGAC
Ripk1b	GACCTGAAGCCTGAGAATATCC	GACCTGAAGCCTGAGAATATCC
Shc1b	GTTGCGCTTCAAACAGTATCTC	GTTGCGCTTCAAACAGTATCTC
Stat3b	GTTCAAGCACCTGACCCTTAG	GTTCAAGCACCTGACCCTTAG
TNFb	AGACCCTCACACTCAGATCA	AGACCCTCACACTCAGATCA
Tnfaip3b	AGAAGAAGCTCAACTGGTGTC	AGAAGAAGCTCAACTGGTGTC
Tollipb	CTCGTTCTACCTTGAGATCTTCG	CTCGTTCTACCTTGAGATCTTCG
Traf2b	ACTTCACCAGAAAGCGTCAG	ACTTCACCAGAAAGCGTCAG
CCL21ac	AAG GCA GTG ATG GAG GGG GT	CTT AGA GTG CTT CCG GGG TG	• 95°C for 1 min • 40 cycles of  o 95°C for 15 secs  o 67°C for 1 min

[Citation: a=(Christophi et al., 2009), b=PrimeTime^® Primers from IDT (Coralville, IA, CA), c=(Kozai et al., 2017)].

Statistical Analysis

Data were analyzed using SigmaPlot14.5 software (Inpixcon, Palo Alto CA). For behavioral data with iTat mice and NCS data, treatment, time and sex were main factors. Three-way analysis of variance (ANOVA) was performed first. If sex differences were not seen in the initial analysis, all data from males and females with the same treatment were combined in the final data analysis using two-way repeated-measures (RM) ANOVA with time and treatment as factors followed by the Holm-Sidak post-hoc test. If sex differences were detected, data were stratified by sex and analyzed within each sex using two-way RM ANOVA with time and treatment as factors followed by the Holm-Sidak post-hoc test. For hind paw IHC data two-way ANOVA with time and sex as main factors followed by the Holm-Sidak post-hoc test was performed. For GFAP IHC, Student-t test was used. Due to the small sample size per sex (n=3), the bioinformatic analysis of the RNA expression data was performed to focus on detecting potential effects of DOX and with male and female data combined for each treatment group. NanoString normalized counts of selected genes from DOX treated mice were analyzed using one-way ANOVA followed by the Holm-Sidak post-hoc test. Similarly, due to small sample size per sex (n=3) for the confirmation qRT-PCR assays of identified genes, statistical power for examining sex difference were low. Therefore, two-way ANOVA with time and treatment as main factors followed by the Holm-Sidak post-hoc test was performed. p-value < 0.05 is considered statistically significant. All statistical results are summarized in Table-2.

Table 2:

Detailed statistical results for all figures

Figure	Method	Factors	F (DF, Residual DF) or t	P value
Figure 2A	Two Way RM ANOVA	Sex	0.0643 (1, 99)	0.083
		Time	0.793 (8, 99)	0.610
		Sex x Time	0.608 (8, 99)	0.769
Figure 2B	Two Way RM ANOVA	Treatment	61.915 (1, 112)	<0.001
		Time	8.857 (8, 112)	<0.001
		Treatment x Time	4.935 (8, 112)	<0.001
Figure 2C	Two Way RM ANOVA	Treatment	45.714 (1, 107)	<0.001
		Time	4.522 (8, 107)	<0.001
		Treatment x Time	2.163 (8, 107)	0.036
Figure 2D	Two Way RM ANOVA	Sex	1.537 (1, 99)	0.234
		Time	0.913 (8, 99)	0.509
		Sex x Time	1.744 (8, 99)	0.098
Figure 2E	Two Way RM ANOVA	Treatment	0.504 (1, 112)	0.490
		Time	1.345 (8, 112)	0.229
		Treatment x Time	4.935 (8, 112)	0.019
Figure 2F	Two Way RM ANOVA	Treatment	0.472 (1, 107)	0.503
		Time	0.500 (8, 107)	0.854
		Treatment x Time	0.332 (8, 107)	0.952
Figure 2G	Two Way RM ANOVA	Sex	0.0497 (1, 99)	0.827
		Time	3.867 (8, 99)	<0.001
		Sex x Time	1.388 (8, 99)	0.211
Figure 2H	Two Way RM ANOVA	Treatment	2.182 (1, 112)	0.162
		Time	2.321 (8, 112)	0.024
		Treatment x Time	1.534 (8, 112)	0.154
Figure 2I	Two Way RM ANOVA	Treatment	11.772 (1, 107)	0.004
		Time	2.048 (8, 107)	0.047
		Treatment x Time	2.099 (8, 107)	0.042
Figure 2J	Two Way RM ANOVA	Sex	0.000596 (1, 99)	0.981
		Time	2.300 (8, 99)	0.026
		Sex x Time	1.409 (8, 99)	0.202
Figure 2K	Two Way RM ANOVA	Treatment	1.449 (1, 112)	0.249
		Time	2.016 (8, 112)	0.051
		Treatment x Time	1.587 (8, 112)	0.137
Figure 2L	Two Way RM ANOVA	Treatment	46.486 (1, 107)	<0.001
		Time	4.797 (8, 107)	<0.001
		Treatment x Time	4.557 (8, 107)	<0.001
Figure 3A	Two Way RM ANOVA	Treatment	0.0805 (1, 199)	0.778
		Time	0.969 (6, 199)	0.448
		Treatment x Time	1.142 (6, 199)	0.340
Figure 3B	Two Way RM ANOVA	Treatment	0.525 (1, 209)	0.473
		Time	3.119 (6, 209)	0.006
		Treatment x Time	1.416 (6, 209)	0.210
Figure 3C	Two Way RM ANOVA	Treatment	0.171 (1, 95)	0.685
		Time	0.839 (6, 95)	0.543
		Treatment x Time	0.392 (6, 95)	0.883
Figure 3D	Two Way RM ANOVA	Treatment	0.0000134 (1, 102)	0.997
		Time	1.449 (6, 102)	0.203
		Treatment x Time	1.348 (6, 102)	0.243
Figure 4A	Two Way ANOVA	Sex	0.846 (1, 79)	0.361
		Time	1.072 (7, 79)	0.389
		Sex x Time	0.732 (7, 79)	0.645
Figure 4B	Two Way ANOVA	Sex	2.208 (1, 79)	0.141
		Time	3.440 (7, 79)	0.003
		Sex x Time	0.898 (7, 79)	0.512
Figure 4C	Two Way ANOVA	Sex	7.464 (1, 79)	0.008
		Time	2.725 (7, 79)	0.014
		Sex x Time	3.238 (7, 79)	0.005
Figure 6A	One Way ANOVA	Time	2.770 (6, 35)	0.026
Figure 6B	Two Way ANOVA	Treatment	0.0125 (1, 74)	0.911
		Time	1.540 (6, 74)	0.015
		Treatment x Time	4.425 (6, 74)	0.177
Figure 6C	One Way ANOVA	Time	3.529 (3, 35)	0.008
Figure 6D	Two Way ANOVA	Treatment	40.537 (1, 74)	<0.001
		Time	3.261 (6, 74)	0.007
		Treatment x Time	4.425 (6, 74)	<0.001
Figure 6E	One Way ANOVA	Time	3.646 (6, 34)	0.007
Figure 6F	Two Way ANOVA	Treatment	354.316 (1, 74)	<0.001
		Time	43.927 (6, 74)	<0.001
		Treatment x Time	43.017 (6, 74)	<0.001
Figure 6G	One Way ANOVA	Time	2.242 (6, 35)	0.062
Figure 6H	Two Way ANOVA	Treatment	60.399 (1, 74)	<0.001
		Time	2.940 (6, 74)	0.013
		Treatment x Time	3.282 (6, 74)	0.006
Figure 7A	Two Way ANOVA	Treatment	90.891 (1, 74)	<0.001
		Time	3.790 (6, 74)	0.002
		Treatment x Time	4.215 (6, 74)	0.001
Figure 7 IHC	Student t-test	Treatment	0.458	0.663

DF = degree of freedom

Results

Tat-induced Neuropathy-Like Behavior

To enable the assessment of Tat-induced neuropathy-like behavioral changes, initial pilot time-response experiments were conducted to determine the best course of treatment with DOX. iTat mice were i.p. injected with DOX at 100 mg/kg for 7, 14, and 21 days respectively and behavioral tests were conducted before DOX injection (day 0) and up to day 35. It was found that a 7-day treatment induced a shorter duration of behavioral changes while a 21-day treatment caused more injection-related side effects and animal mortality, therefore, a 14-day treatment regimen was used in all experiments thereafter (Cao, 2019). All behavioral tests were performed on days 0 (naïve), 3, 7, 14, 21, 28, and 35. To assess neuropathy-like behavioral changes following Tat induction by DOX, we performed a series of sensory sensitivity tests and a grip strength test (assessing motor function) using iTat mice treated with DOX and PBS. Effects of DOX that were not associated with the Tat transgene were evaluated using C57BL/6J WT mice injected with DOX. Overall, no significant DOX-induced effects were observed in either male or female WT mice except a transient increase of cold sensitivity in male mice at day 3 post-DOX injection (Figures 2 A, D, G, and J; mechanical sensitivity, 2A two-way RM ANOVA, p_time = 0.610, p_sex = 0.803, p_timexsex = 0.769; heat sensitivity, 2D two-way RM ANOVA, p_time = 0.509, p_sex = 0.234, p_timexsex = 0.098; cold sensitivity, 2G two-way RM ANOVA, p_time < 0.001, p_sex = 0.827, p_timexsex = 0.211 with post hoc Holm-Sidak test showing p < 0.05 for male day 3 vs. male day 0 and female day 3; grip strength, 2J two-way RM ANOVA, p_time = 0.026, p_sex = 0.981, p_timexsex = 0.202 without detecting any individual group differences via the post hoc Holm-Sidak test).

Figure 2. Development of neuropathy-like behaviors following Tat induction in iTat mice.

Both male (B, E, H, and K) and female (C, F, I, and L) iTat mice were subjected to either Dox or PBS daily i.p. injections from days 0–13. C57BL/6 WT mice (A, D, G, and J) were injected with Dox daily concurrently as controls. All mice were tested for the development of neuropathy-like behaviors: mechanical sensitivity (A-C), heat sensitivity (D-F), cold sensitivity (G-I), and hind paw grip strength (J-L). All data are presented as mean±SEM, n=8/group/sex. Appropriate ANOVAs followed by Holm-Sidak post-hoc tests were performed. * p<0.05 vs. corresponding day 0, # p<0.05 vs. corresponding PBS group at the same time, and & p<0.05 vs. corresponding WT female group at the same time.

Next, we examined the effect of Tat-associated neuropathic-like behavioral changes by comparing behavioral responses between DOX vs. PBS treated iTat mice. An initial three-way ANOVA using sex, time, and treatment as factors suggested sex differences in most of the behavioral measures we performed. Therefore, for each behavioral test, data were stratified based on sex and two-way RM ANOVA using time and treatment as factors within each sex followed by the Holm-Sidak post hoc test was performed. For mechanical sensitivity test, in both male and female iTat mice, there were significant time and treatment effects, as well as the interaction between time and treatment (Figures 2 B and C, male 2B two-way RM ANOVA, p_time < 0.001, p_treatment < 0.001, p_{timextreatment} < 0.001; female 2C two-way RM ANOVA, p_time < 0.001, p_treatment < 0.001, p_{timextreatment} = 0.036). DOX-treated male and female iTat mice showed significantly increased mechanical sensitivity from day 3 to day 35 post DOX injection compared to respective day 0 levels, as well as compared to corresponding PBS control groups, while PBS did not induce significant changes in mechanical sensitivity (Figures 2B and C, Holm-Sidak post hoc test, p < 0.05 for indicated individual group comparisons). For heat sensitivity, overall, no significant time or treatment effects were seen in either males or females (Figures 2 E and F, male 2E two-way RM ANOVA, p_time = 0.229, p_treatment = 0.490, p_{timextreatment} = 0.019; female 2F two-way RM ANOVA, p_time = 0.854, p_treatment = 0.503, p_{timextreatment} = 0.952), except DOX-treated males showed slightly reduced withdrawal latency than PBS controls at day 35 (Figure 2E, Holm-Sidak post hoc test, p < 0.05). Sex-dependent behavioral changes were most notable with the cold sensitivity test and hind paw grip strength test. For the cold sensitivity test, females were significantly affected by both time and treatment with DOX mice showing significantly increased cold sensitivity at multiple time points when compared to PBS controls, whereas male mice were only affected by time, with DOX mice having increased cold sensitivity only at days 3 and 21 compared to PBS mice (Figures 2 H and I, male 2H two-way RM ANOVA, p_time = 0.024, p_treatment = 0.162, p_{timextreatment} = 0.154; female 2I two-way RM ANOVA, p_time = 0.047, p_treatment = 0.004, p_{timextreatment} = 0.042; both 2H and 2I, Holm-Sidak post hoc test, p < 0.05 for indicated individual group comparisons). For grip strength, no significant effect from time or treatment was observed in males (Figure 2K, two-way RM ANOVA, p_time = 0.051, p_treatment = 0.249, p_{timextreatment} = 0.137), while in females, DOX treatment significantly reduced hind paw strength (Figures 2L, two-way RM ANOVA, p_time < 0.001, p_treatment < 0.001, p_{timextreatment} < 0.001 with Holm-Sidak post hoc test, p < 0.05 for indicated individual group comparisons).

Tat-induced changes in nerve conduction properties

To assess potential Tat induced neuropathy-like physiologic changes, we performed nerve conduction studies at days 0 (naïve), 3, 7, 14, 21, 28, and 35 along the sciatic nerve in iTat mice treated with DOX compared to iTat mice treated with PBS from days 0–13 as described earlier (10 males and 10 females per treatment group were used from 4 independent sets of experiments). First, sex differences were only detected in latency at the maximal CMAP (Three-way ANOVA, p_sex <0.05) but not the amplitude or duration at the CMAP (Three-way ANOVA, p_sex >0.05), therefore, further analyses were performed with data from males and females combined for maximal amplitude (Figure 3A) and duration (Figure 3B), while with data from males and females were separated for latency (Figures 3C and D). No significant treatment or time effects were detected for maximal amplitude (Figure 3A, n=20, Two-Way RM ANOVA, p_treatment = 0.778, p_time = 0.448, p_{treatmentxtime} = 0.340) or latency for either sex (Figure 3C, males, n=10, Two-Way RM ANOVA, p_treatment = 0.685, p_time = 0.543 p_{treatmentxtime} = 0.883; Figure 3D, females, n=10, Two-Way RM ANOVA, p_treatment = 0.997, p_time = 0.203, p_{treatmentxtime} = 0.243)_. A time effect was detected for duration, with the PBS control group showing a transient increase in duration of the CMAP at day 21 (Figure 3B, n=20, Two-Way RM ANOVA, p_treatment = 0.473, p_time = 0.006, p_{treatmentxtime} = 0.210). However, given the fluctuation of in vivo animal studies, the biological meaning of this statistical change in PBS (pH matched at 3) controls is not clear and cannot be ascertained based on our current data.

Figure 3. Nerve conduction studies following Tat induction in iTat mice.

Nerve conduction studies were performed with left side sciatic nerve in both male and female iTat mice subjected to either DOX or PBS daily i.p. injections from days 0–13. At indicated times, sciatic nerve conduction parameters: maximal amplitude (A), duration of the maximal amplitude (B), and latency at the maximal amplitude (C and D) were recorded. All data are presented as mean±SEM, n=10/group/sex. Appropriate ANOVAs followed by Holm-Sidak post-hoc tests were performed. Sex difference was detected only for the latency; thus, data are presented for each sex separately. * p<0.05 vs. corresponding day 0.

Tat-induced changes in hind paw IENF density

The average hind paw (left and right) IENF density was examined in both male and female iTat mice treated with DOX from days 0–13 as described earlier at days 0 (naïve), 3, 7, 14, 21, 28, and 35, as well as mice treated with PBS at day 14. Consistent with previous report (Han et al., 2021), the density of the total nerve fibers represented by PGP9.5+ nerve fibers showed no changes following Tat induction in either males or females, which was similar to the levels in respective PBS treated mice. No sex differences were observed in PGP9.5 IENF density (Figure 4A, two-way ANOVA, p_time=0.389, p_sex=0.361, and p_timexsex=0.645). In contrast, there was a small but statistically significant effect by time but not sex for CGRP+ IENF density, i.e. the density of CGRP+ nerve fibers significantly increased at day 21 compared to both day 0 and PBS treated mice regardless of sex (Figure 4B, two-way ANOVA, p_time=0.003, p_sex=0.141, and p_timexsex=0.512). A post hoc test also indicated a faster reduction of CGRP IENF density in females than in males (Figure 4B, Holm-Sidak post-hoc test, p<0.05 between sex at day 35). As a result, the ratio between CGRP+ and PGP9.5+ IENF density was significantly affected by both time and sex (Figure 4C, two-way ANOVA, p_time=0.014, p_sex=0.008, and p_timexsex=0.005). In the females, the ratio increased after Tat induction and peaked at day 21, while in the males, the ratio has a gradual but not statistically significant increasing trend.

Figure 4. Changes in hind paw IENF density following Tat induction in iTat mice.

Both male and female iTat mice were subjected to DOX daily i.p. injections from days 0–13 and hind paw samples were collected from both sides on days 0, 3, 7, 14, 21, 28, and 35. Separate control groups of male and female iTat mice were injected with PBS and collected on day 14. The average numbers of PGP9.5+ (A) and CGRP+ (B) IENF/mm hind paw skin were determined via IHC. The ratio of CGRP/PGP9.5 IENF density is presented in C. All data are presented as mean±SEM, n=5–7/group/sex. Two-way ANOVA followed by Holm-Sidak post-hoc tests were performed. # p<0.05 vs. corresponding male group at the same time, and & p<0.05 vs. PBS group of the same sex. * p<0.05 vs. corresponding day 0 and PBS group regardless of sex. D and E show the representative images from all treatment groups (including naïve, DOX, and PBS) and both sexes (male and female) iTat mice to illustrate the IHC staining for PGP9.5 (D) and CGRP (E), respectively. Arrows indicate positive IENFs. (20x, Scale bar = 100 μm).

Tat-induced changes in expression on inflammation-related genes in lumbar spinal cord

Lumbar spinal cord RNA was isolated from iTat mice treated with DOX at days 0 (naïve), 3, 7, 14, 21, 28, and 35, and iTat mice treated with PBS at day 14. A NanoString assay was used to profile expression of inflammation-related RNA. As described in Materials and Methods, the time course changes of average relative expression from each treatment group were clustered via STEM program, which identified four significant temporal expression profiles: cluster 17 (13 genes) – expression increased transiently early post-Tat induction, cluster 41 (15 genes) – expression increased transiently mid-time post-Tat induction, cluster 37 (13 genes) – expression increased later, and cluster 10 (57 genes) – expression declined overtime post-Tat induction (Figure 5A). Follow-up PANTHER Gene Ontology-pathway analysis of the STEM-identified gene clusters recognized a total of 69 pathways that were potentially regulated by Tat induction (Table 3). Three pathways were common across all four clusters, which were the inflammation mediated by chemokines and cytokines, the apoptosis, and the TLR signaling pathways. We chose to focus on these pathways for the follow-up study. A summary of the 38 identified genes that were part of any of the 4 clusters and were associated with each of the 3 major biological pathways are shown in Figure 5B.

Figure 5. STEM clusters and the list of the genes associated with each of the 3 key signaling pathways identified through PANTHER pathway analysis.

(A) shows the four significant temporal expression gene clusters that were identified by STEM. PANTHER pathway analysis recognized 3 major biological pathways that were common across all four gene clusters. A summary of specific genes that were identified to be associated with each of these 3 pathways is shown in (B). Cluster ID for each gene is shown within the parentheses. These genes underwent further verification via qRT-PCRs.

Table 3:

Pathways recognized through PANTHER Gene Ontology-pathway analysis of STEM-identified gene clusters

	Cluster 17 (Early-peak expression)	Cluster 41 (Mid-peak expression)	Cluster 37 (Late-peak expression)	Cluster 10 (Declining expression)
Genes in cluster	C1s, C8A, CCL20, CCL21A, CXCL9, FXYD2, HSH2D, IRF3, LTA, MEF2C, OAS2, OASL1, RETNLA	ALOX12, C3AR1, C9, CXCR4, HDAC4, IFNA1, IL1R1, MAFK, MAP3K9, MEF2D, MYL2, RELA, STAT3, TNFAIP3, TOLLIP	CCL17, CCL19, CCL5, CHI3L3, FLT1, IRF1, MAP3K1, MKNK1, NOD1, NOD2, SHC1, STAT2, TRAF2	ATF2, BCL2L1, C2, CCL11, CCL22, CCL24, CREB1, ELK1, GNAQ, GNB1, GNGT1, HC, HMGB1, HMGB2, HMGN1, HRAS1, IFIT2, IFNG, IL10, IL18, IL1RN, IL21, IL6, IL7, JUN, KEAP1, KNG1, LIMK1, MAFG, MAP2K4, MAP3K7, MAPK1, MAPK3, MAPK8, MEF2A, MMP3, MX1, MX2, MYD88, NFATC3, NOS2, NOX1, PRKCA, PRKCB, PTGER2, PTGER3, RAPGEF2, RHOA, RIPK1, ROCK2, RPS6KA5, SMAD7, TCF4, TLR7, TNF, TNFSF14, TSLP
Signaling pathways identified
Shared by 4 clusters	• Apoptosis signaling pathway • Inflammation mediated by chemokine and cytokine signaling pathway • Toll receptor signaling pathway
Shared by 3 clusters		Angiogenesis, CCKR signaling map, EGF receptor signaling pathway, Gonadotropin-releasing hormone receptor pathway, Interleukin signaling pathway, p38 MAPK pathway, PDGF signaling pathway, Ras pathway
Shared by 2 clusters		JAK/STAT signaling pathway FGF Signaling Pathway; Integrin signaling pathway; Oxidative stress response; p53 pathway; T Cell activation	JAK/STAT signaling pathway	FGF Signaling pathway; Integrin signaling pathway; Oxidative stress response; p53 pathway; T Cell activation
Not shared by other clusters		Axon guidance mediated by Slit/Robo		5-HT1, 5-HT2, and 5-HT4 type receptor mediated signaling pathways; Alpha adrenergic receptor signaling pathway; Alzheimer disease-amyloid secretase pathway; Alzheimer disease-presenilin pathway; Angiotensin II-stimulated signaling through G proteins and beta-arrestin; Axon guidance mediated by netrin; Axon guidance mediated by semaphorines; B Cell Activation; Beta1, Beta2, and Beta3 adrenergic receptor signaling pathways; Blood coagulation; Cadherin signaling pathway; Corticotropin releasing factor receptor signaling pathway, Cytoskeletal regulation by Rho GTPase; Dopamine receptor mediated signaling pathway; Endogenous cannabinoid signaling; Endothelin signaling pathway; Enkephalin release; FAS signaling pathway; GABA-B receptor II signaling; Heterotrimeric G-protein signaling pathway-Gi alpha and Gs alpha mediated pathway; Heterotrimeric G-protein signaling pathway-Gq alpha and Go alpha mediated pathway; Heterotrimeric G-protein signaling pathway-rod outer segment phototransduction; Histamine H1 receptor mediated signaling pathway; Histamine H2 receptor mediated signaling pathway; Huntington disease; Insulin/IGF Pathway-mitogen activated protein kinase kinase/MAPkinase cascade; Interferon-gamma signaling pathway; Metabotropic glutamate receptor group I, II, and III pathways; Muscarinic acetylcholine receptor 1 and 3 signaling pathway; Muscarinic acetylcholine receptor 2 and 4 signaling pathway; Nicotine pharmacodynamics pathway; Opioid prodynorphin, proenkephalin, and proopiomelanocortin pathways; Oxytocin receptor mediated signaling pathway; p53 pathway feedback loops 2; Parkinson disease; PI3 kinase pathway; Plasminogen activating cascade; TGF-beta signaling pathway; Thyrotropin-releasing hormone receptor signaling pathway; Toll pathway-drosophila; Transcription regulation by bZIP transcription factor; VEGF signaling pathway; Wnt signaling pathway

Validation qRT-PCR was performed for all above 38 genes from the 3 major identified pathways. PBS treated animals were included to verify DOX-induced changes over time. Time course changes in these genes were graphed using both qRT-PCR data (percentage change in Ct-based relative expression to GAPDH, day 0 = 100%) and NanoString data (count-based relative expression to housekeeping gene sets, time-course data are only available for DOX groups) with two sexes combined (due to small sample size per sex, see Materials and Methods), and the expression patterns were compared for each gene. Two-way ANOVA analyses with post hoc tests were performed for the qRT-PCR data using time and treatment as factors; One-way ANOVA with post-hoc tests were performed for NanoString data. Among the 38 genes, 4 genes exhibited similar expression patterns between qRT-PCR and NanoString assays for DOX groups, while also displaying statistically significant time and/or treatment effects (Figure 6). Of these 4 genes, 2 genes (Alox12, and Cxcr4) (Figures 6A–D, 6A Alox12 NanoString data, one-way ANOVA, p_time =0.026; 6B Alox12 qRT-PCR data, two-way ANOVA, p_time=0.015, p_treatment=0.911, and p_{timextreatment}=0.177; 6C Cxcr4 NanoString data, one-way ANOVA, p_time =0.008; 6D Cxcr4 qRT-PCR data, two-way ANOVA, p_time=0.007, p_treatment<0.001, and p_{timextreatment}<0.001) were associated with the inflammation mediated by chemokines and cytokines signaling pathway, 1 gene (TRAF2) (Figures 6E and F, 6E TRAF2 NanoString data, one-way ANOVA, p_time =0.007; 6F TRAF2 qRT-PCR data, two-way ANOVA, p_time<0.001, p_treatment<0.001, and p_{timextreatment}<0.001) was associated with the apoptosis pathway, and 1 gene was associated with the TLR pathways (TOLLIP) (Figures 6G and H, 6G TOLLIP NanoString data, one-way ANOVA, p_time =0.062; 6H TOLLIP qRT-PCR data, two-way ANOVA, p_time=0.013, p_treatment<0.001, and p_{timextreatment}=0.006). Except for TRAF2, which showed a continued dramatic increase (up to about 90-fold) and plateaued at day 14, all other genes displayed a transient increase with Cxcr4 peaking at day 7, Alox12 peaking at day 14, and TOLLIP peaking between days 14–21 post-Tat induction and ranged from a 2- to 4-fold change compared with day 0 levels.

Figure 6. Changes in selected inflammation-related genes within lumbar spinal cord following Tat induction in iTat mice.

Both male and female iTat mice were subjected to DOX or pH-matched PBS daily i.p. injections from days 0–13 and lumbar spinal cord samples were collected on days 0, 3, 7, 14, 21, 28, and 35. RNA was isolated followed by qRT-PCR assay. Percentage changes in relative expression comparing to respective day 0 level are shown for selected genes (right side, n=6/group (3 males + 3 females) for DOX and PBS groups; n=8 (5 males + 3 females) for naive group) along with corresponding gene expression results (normalized counts) from the NanoString assay with DOX-treated animals (left side, n=3/time point/sex). Text on the right side indicates identified signaling pathways to which each gene belongs to according to PANTHER pathway analysis. All data are presented as mean±SEM. Appropriate ANOVA analysis was performed followed by Holm-Sidak post-hoc tests. * p<0.05 vs. corresponding day 0, # p<0.05 vs. PBS controls on the same day, and & p<0.1 vs. corresponding day 0.

GFAP+ astrocytes within the spinal cord are the primary source of Tat and potential source of the detected inflammatory factors. We further evaluated GFAP expression within the lumbar spinal cord at RNA level within the same tissues used above and lumbar spinal cord GFAP expression at the protein level (Figure 7). DOX-treated mice showed increased GFAP RNA expression and greater overall expression compared to PBS-treated mice (Figure 7A, two-way ANOVA, p_time=0.002, p_treatment<0.001, and p_{timextreatment}=0.001). At day 14 post-Tat induction, GFAP expression represented by integrated density via IHC was only minimally, but not statistically significantly, greater in DOX vs. PBS treated mice (Student-t test, p>0.05) (Figure 7B and C).

Figure 7. Changes in GFAP expression following Tat induction in iTat mice.

Both male and female iTat mice were subjected to DOX or pH-matched PBS daily i.p. injections from days 0–13 and lumbar spinal cord samples were collected on days 0, 3, 7, 14, 21, 28, and 35. RNA was isolated followed by qRT-PCR assay. Percentage changes in relative expression comparing to respective day 0 level are shown for GFAP (A). Data are presented as mean±SEM [n=6/group (3 males + 3 females) for DOX and PBS groups; n=8 (5 males + 3 females) for naive group]. Two-way ANOVA followed by Holm-Sidak post-hoc tests were performed. * p<0.05 vs. corresponding day 0, and # p<0.05 vs. PBS controls on the same day. B and C show the representative images from day 14 PBS (B) and DOX (C) treated iTat mice respectively (n=4 with 2 males+2 females per group) to illustrate the IHC staining for GFAP. (20x, Scale bar = 100 μm).

Discussion

Our study helps further establish the notion that HIV Tat contributes to the development of HIV-associated neuropathy, including sex-dependent neuropathy-like symptoms. Consistent with what has been reported by others with doxycycline-inducible Tat transgenic mice (Toma et al., 2022, Wodarski et al., 2018, Han et al., 2021), we showed that in our model of iTat mice, doxycycline injection significantly induced mechanical hypersensitivity but not heat hypersensitivity. Due to this lack of Tat-induced heat hypersensitivity, further tail hot water immersion testing was not considered even though the tail immersion test can help assess spinal reflex mediated pain-like behaviors (Deuis et al., 2017). In addition, for the first time, we showed that DOX-injected iTat mice also showed significant cold hypersensitivity tested via dry ice-cold plantar test and reduced hind paw grip strength in predominantly female mice. The association between HIV Tat and behavioral manifestations of neuropathy was further established by the fact that WT B6 mice receiving doxycycline did not show significant changes in any of the behavioral tests. However, unlike what has been shown by others either using a different iTat model or different recording strategies (Toma et al., 2022, Han et al., 2021), nerve conduction studies on sciatic nerve with the parameters we measured did not indicate correlative physiological changes following Tat induction (either males or females) in our model with our Tat induction regimen despite a small but significant increase of numbers of CGRP-positive peptidergic IENFs in both male and female iTat mice. Altogether, our observations suggest the contribution of Tat to selected but not all aspects of HIV-associated neuropathy. This is not surprising as HIV neuropathy can manifest with various symptoms (JohnsHopkinsMedicine, 2025) and it has been shown that other viral proteins, such as gp120, also contribute to the development of HIV neuropathy (Wallace et al., 2007b, Yuan et al., 2014, Zheng et al., 2011, Herzberg and Sagen, 2001, Ledeboer et al., 2005, Milligan et al., 2000, Minami et al., 2003, Wallace et al., 2007a). Unlike Tat, centrally administered gp120 is known to induced heat hypersensitivity (Milligan et al., 2000), while similarly to Tat, gp120 cannot be attributed as the sole viral factor of HIV neuropathy as perineural gp120 administration did not induce cold sensitivity (Wallace et al., 2007a, Wallace et al., 2007b) and overexpression of gp120 in the CNS alone did not cause signs of HIV neuropathy (Keswani et al., 2006). Future studies with iTat mice will help to determine specifically how Tat contributes to HIV neuropathy. Additionally, besides Tat and gp120, other HIV proteins such as Vpr have previously been shown to contribute to HIV neuropathy (Acharjee et al., 2010). While most reports usually focus on one particular HIV protein, HIV transgenic rats that express a mixture of HIV associated proteins also exhibited neuropathic pain-like behaviors (Gryshyna et al., 2023). It is reasonable to expect these HIV proteins may work synergistically through acting on different sites of the nervous system (Peripheral vs. central nervous systems) and/or on the same targets such as glial cells or DRG neurons to promote the development of HIV neuropathy. However, specific studies are needed to verify this phenomenon.

Sex-dependent changes in Tat-associated HIV neuropathy appear to be common between the two current doxycycline-inducible Tat transgenic mouse models: the Nath model (Bruce-Keller et al., 2008, Chauhan et al., 2003) and the He model (Kim et al., 2003), despite their differences in mouse backgrounds, sources of HIV Tat peptides, numbers of copies of HIV Tat inserted, and the progression of HIV-associated pathologies. The Nath model has been characterized regarding Tat’s association to neuropathy in more detail. Consistent with observations in the Nath model, using the He model, we also saw sex-dependent changes, particularly in cold-hypersensitivity and reduced grip strength, both of which were significant only in females, but not in mechanical sensitivity (Toma et al., 2022). Similar to previous reports, Tat-induced changes in IENF density did not seem to be sex-dependent (Toma et al., 2022, Wodarski et al., 2018). Further, in the Nath model, females were shown to be more resistant to morphine and gabapentin treatment of established Tat-associated neuropathy (Toma et al., 2022) and males experienced reduced neuropathy symptoms when they underwent additional insults from induction of either inflammatory pain or neuropathic pain (Bagdas et al., 2020). All of these observations indicate that factors unique to females may contribute to the development of cold hypersensitivity and reduced grip strength following Tat induction, and potentially differential responses to additional pain modulations. Further, differential cold sensitivity may be specific to Tat-associated neuropathy as HIV transgenic rats that express a mix of viral proteins within the constructed non-infectious provirus displayed similar cold hypersensitivity between males and females (Gryshyna et al., 2023). Whether sex-dependent differences are unique to Tat-associated neuropathy compared to gp120 is unknown. Unfortunately, sex differences were not assessed in early studies with gp120 administration (Herzberg and Sagen, 2001, Milligan et al., 2000, Wallace et al., 2007a, Wallace et al., 2007b, Yuan et al., 2014, Zheng et al., 2011).

The clinical importance of cold sensitivity was demonstrated by a report in which an increase in cold pain sensitivity was only observed in patients with painful HIV neuropathy but not in patients with non-painful HIV neuropathy, while cold sensory perception was reduced in both groups (Martin et al., 2003), suggesting the clinical relevance of Tat-associated neuropathy. Cold nociceptors have been shown to be capsaicin-sensitive (McKemy, 2018). Therefore, the observed increase in CGRP+ IENF may contribute to the cold hypersensitivity. However, this increase of CGRP+ fibers was not observed until day 21 and showed a faster reduction in females, suggesting changes in CGRP+ IENF alone cannot explain changes in sex-dependent cold sensitivity, and additional mechanistic processes are likely to be involved. These could be related to expression and function of TRPM8 and TRPA1 channels as well as several Nav channels such as Nav1.8, Nav1.9, and Nav1.6 (McKemy, 2018), all of which could be further investigated in iTat mice, particularly males vs. females.

Inflammation has been long associated with HIV neuropathy, both peripherally at the DRG and peripheral nerve levels and centrally at the spinal cord level, and it can be mediated through proinflammatory cytokines and chemokines, such as IL-1-beta, TNF-alpha, and CCL2, and chemokine receptors, such as CCR2, CCR5, CXCR4, and CX3CR1, as well as spinal cord glial activation (Hao, 2013, Liu et al., 2012, Lu et al., 2021). Changes in plasma levels of proinflammatory chemokine CCL5 has been associated with HIV neuropathy in patients (Chew et al., 2011). However, the underlying mechanism involved in the development of Tat-associated HIV neuropathy has not been explored as extensively as that for gp120-associated neuropathy. So far, similar to gp120 models, iTat mice with Tat induction displayed correlative microglial responses and differential expression of selected inflammatory molecules within the spinal cord and DRGs have been observed with the Nath model (Bruce-Keller et al., 2008, Chauhan et al., 2003, Toma et al., 2022, Yuan et al., 2014, Milligan et al., 2000, Wallace et al., 2007a). Mitochondrial changes have been suggested but not directly investigated in gp120 neuropathy models (Roda et al., 2021, Roda and Hoke, 2019). However, abnormal sciatic nerve-associated mitochondrial changes were observed in the He model of iTat mice (Kim et al., 2003). Furthermore, extensive investigations regarding the astrocytic contribution to gp120-associated neuropathy, including the Wnt5a-mediated neuro-astrocyte signaling (Tang, 2022, Wallace et al., 2007a, Li et al., 2013, Yuan et al., 2015), and glial regulating agents were shown to be effective in reducing gp120-induced neuropathic pain like behaviors (Milligan et al., 2000, Wallace et al., 2007a). On the other hand, despite that direct hippocampal injection of Tat induced astrogliosis and Tat-induction induced augmented GFAP immunoreactivity within the brain of the He model of iTat mice (Kim et al., 2003, Harricharan et al., 2015), only a slight but not statistically significant increase in GFAP expression was observed in the spinal cord of the Nath model of iTat mice (Wodarski et al., 2018), which is consistent with our results shown in Figure 7 using the He model. Therefore, astrocytic contributions to iTat-associated neuropathy remains to be elucidated. Nonetheless, given that HIV Tat has been shown to induce production of proinflammatory cytokines following direct brain injection in vivo (Lawson et al., 2011) and when administered to astrocytes and microglia in vitro, respectively (Nookala et al., 2013, Kiebala and Maggirwar, 2011), microglia and astrocytes remain possible cellular sources and/or driving forces facilitating the actions of inflammatory factors in the spinal cord in our model, as for various gp120 models (Tang, 2022).

In this initial investigation, taking advantage of the predominant central production of Tat in the iTat mice to systematically detect potential inflammation-related mechanisms at the spinal cord level, we performed NanoString analysis for 200+ inflammation related genes, followed by bioinformatic approaches. Three major inflammation-related pathways along with 38 associated genes were identified. Four genes were further verified through qRT-PCR. First, as described earlier, cytokines/chemokines have long been associated with HIV neuropathy and it is not surprising cytokine/chemokine-mediated inflammation was identified as one of the three major pathways. Cxcr4, a HIV co-receptor, has been implicated in HIV neuropathy mainly through animal models (Liu et al., 2012). Alox12 (arachidonate 12-lipoxygenase), metabolizing arachidonic acid to generate proinflammatory lipid mediators, has been shown to contribute to diabetic neuropathy and associated axonal degeneration in animal models (Obrosova et al., 2010, Rudhard et al., 2015). In our study, these identified inflammatory factors were found to be transiently increased at different times after Tat induction, suggesting their unique yet collaborative contribution to the development of Tat neuropathy. Second, unlike the above pro-inflammatory factors, TOLLIP (toll interacting protein) is a known TLR pathway modulator and specifically suppresses IL-1 receptor-associated kinase (IRAK)1 to reduce activation of MyD88-mediated pathways (Zhang and Ghosh, 2002). To date, despite the possibility that TLR pathways could be the upstream regulators for the production of many proinflammatory cytokines and the activation of MAPK pathway that are associated with HIV neuropathy (Hao, 2013, Liu et al., 2012, Lu et al., 2021, Kanehisa_Laboratories, 2017), specific studies on roles of TLR pathways in HIV neuropathy have not been reported. The observed increase of TOLLIP may suggest its role in regulating inflammation during Tat neuropathy. Finally, it is also expected that apoptotic pathway is critical in HIV neuropathy. Tat-induced neurotoxicity has been shown in vitro using human fetal brain cells (Chauhan et al., 2003). Sensory neuron damage and apoptosis have been implicated in a gp120-associated neuropathy model (Wallace et al., 2007a). TRAF2 (TNF receptor associated factor 2), a member of the TNF receptor associated factor protein family, has been shown to be involved in complex signaling pathways in a context-dependent manner (Siegmund et al., 2022) and predominantly as an anti-apoptotic factor (Ye et al., 2021, Etemadi et al., 2015, Kreckel et al., 2019, Guo et al., 2017). One may postulate that proinflammatory factors promote neuronal damage and apoptosis, while steady increasing of TRAF2, potentially induced by TOLLIP upregulation, actively antagonizes these damaging processes during Tat neuropathy. On the other hand, TRAF2 may act in conjunction with other proinflammatory factors to promote Tat neuropathy as suggested in a diabetic neuropathy model (Chen et al., 2019). Note that due to the relatively small sample size, potential sex-dependent changes in gene expression could not be assessed at this time. Future research will determine whether any of these genes and their related pathways could be contributing to any of the observed sex differences. Altogether, our results represent an initial exploration of potential inflammatory changes involved in Tat-associated neuropathy and many of these identified genes have not been extensively studied in HIV neuropathy. Whether and how these changes contribute to the associated neuropathic pain specifically require further investigation, particularly via factor-specific studies using both pharmacological and genetic (knockout and overexpression) approaches.

It should be noted that GFAP is not exclusively expressed by astrocytes in the CNS. GFAP expression has been observed in satellite glia cells and non-myelinating Schwann cells within DRGs, particularly following peripheral nerve injury and under an inflammatory condition (Konnova et al., 2023, Mohr et al., 2021). Therefore, in the iTat mice, DOX injection could stimulate Tat expression within DRGs, which in turn could act directly on the DRG neurons and contribution to Tat-associated painful neuropathy (Chi et al., 2011). This can be investigated both in vivo and in vitro in future studies.

The major limitations of this study are consistent with the directions for future investigations. In this study, we identified potential inflammatory pathways that contribute to the development of Tat-neuropathy through RNA profiling. Changes in protein levels of the above identified molecules need to be further determined before pharmacological and genetic tools can be employed. Cellular sources of these inflammatory factors also require further determination. Due to the small sample size with the RNA profiling study, potential involvement of identified pathways in sex-dependent behavioral changes could not be assessed. Further, to keep our study focused in the spinal cord changes, we did not examine the potential roles of non-astrocytic GFAP-expressing cells in Tat-neuropathy. In addition, other HIV proteins, such as gp120, are known to contributing to the development of HIV neuropathy. The current study did not examine potential interactions between Tat and other viral components in HIV neuropathy.

In summary, our study provides additional evidence to establish that HIV Tat contributes to the development of HIV neuropathy. We also further demonstrated that iTat mice can serve as a model system to help investigate unique neuropathy-like symptoms induced by HIV Tat. Particularly, sex-dependent mechanisms in HIV neuropathy could be realized using iTat mice given the consistent sex-dependent neuropathy-like behaviors in iTat mice. Through bioinformatic analysis, we have identified several novel inflammation-related pathways and related factors that can be further investigated to facilitate mechanistic studies related to Tat neuropathy. However, it should be noted that Tat-associated neuropathy may not reflect all aspects associated with HIV neuropathy as many other HIV-related factors act together with Tat induce HIV neuropathy.

Highlights.

• A doxycycline-inducible Tat transgenic mouse model was used to study HIV neuropathy.

• Tat contributes to HIV neuropathy, including sex-dependent neuropathy-like changes.

• Spinal cord RNA profiling suggests involvement of 3 key inflammation pathways.

Abbreviations

Alox12

Arachidonate 12-lipoxygenase

ANOVA

Analysis of variance

AVMA

American Veterinary Medical Association

CNS

Central nervous system

CGRP

Calcitonin gene related peptide

CMAP

Compound muscle action potential

DOX

Doxycycline hyclate

DRG

Dorsal root ganglion

GFAP

Glial fibrillary acidic protein

IACUC

Institutional Animal Care and Use Committee

IENF

Intraepidermal nerve fiber

IHC

Immunohistochemistry

i.p.

Intraperitoneally

IRAK

IL-1 receptor-associated kinase

iTat mice

Doxycycline-inducible HIV Tat transgenic mice

NCS

Nerve conduction study

NMDA

N-methyl-D-aspartate

PBS

Phosphate-buffered saline

RM

Repeated-measures

STEM

Short Time-Series Expression Miner Program

Tat

Trans-Activator of Transcription

TLR

Toll-like receptor

TOLLIP

Toll interacting protein

TRAF2

TNF receptor associated factor 2

WT

Wild type

Data Availability Statement

The data supporting this study’s findings are available from the corresponding author upon reasonable request.