Early ultrasonic vocalization deficits and related thyroarytenoid muscle pathology in the transgenic TgF344-AD rat model of Alzheimer’s disease
Data files
Nov 19, 2024 version files 5.90 MB
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AD_pilot_-__Gene_Expression_Results_-_Bar_Chart.xlsx
25.28 KB
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AD_pilot.mgxd
16.61 KB
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ADCohort2_USVs_v2.xlsx
5.52 MB
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ADpilot_Image.bmp
110.95 KB
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biorad.r
8.78 KB
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PER__CT.txt
203.23 KB
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README.md
21.94 KB
Abstract
Alzheimer’s disease (AD) is a progressive neurologic disease and the most common cause of dementia. Classic pathology in AD is characterized by inflammation, abnormal presence of tau protein, and aggregation of β-amyloid that disrupt normal neuronal function and lead to cell death. Deficits in communication also occur during disease progression and significantly reduce health, well-being, and quality of life. Because clinical diagnosis occurs in the mid-stage of the disease, characterizing the prodrome and early stages in humans is currently challenging. To overcome these challenges, we use the validated TgF344-AD (F344-Tg(Prp-APP, Prp-PS1)19/Rrrc) transgenic rat model that manifests cognitive, behavioral, and neuropathological dysfunction akin to AD in humans. The overarching goal of our work is to test the central hypothesis that pathology and related behavioral deficits such as communication dysfunction in part manifest in the peripheral nervous system and corresponding target tissues already in the early stages. The primary aims of this study are to test the hypotheses that: (1) changes in ultrasonic vocalizations (USV) occur in the prodromal stage at 6 months of age and worsen at 9 months of age, (2) inflammation as well as AD-related pathology can be found in the thyroarytenoid muscle (TA) at 12 months of age (experimental endpoint tissue harvest), and to (3) demonstrate that the TgF344-AD rat model is an appropriate model for preclinical investigations of early AD-related vocal deficits. USVs were collected from male TgF344-AD (N = 19) and wildtype (WT) Fischer-344 rats (N = 19) at 6 months (N = 38; WT: n = 19; TgF344-AD: n = 19) and 9 months of age (N = 18; WT: n = 10; TgF344-AD: n = 8) and acoustically analyzed for duration, mean power, principal frequency, low frequency, high frequency, peak frequency, and call type. RT-qPCR was used to assay peripheral inflammation and AD-related pathology via gene expressions in the TA muscle of male TgF344-AD rats (n = 6) and WT rats (n = 6) at 12 months of age. This study revealed a significant reduction in the mean power of ultrasonic calls from 6 to 9 months of age and increased peak frequency levels over time in TgF344-AD rats compared to WT controls. Additionally, significant downregulation of AD-related genes Uqcrc2, Bace2, Serpina3n, and Igf2, as well as downregulation of pro-inflammatory gene Myd88 was found in the TA muscle of TgF344-AD rats at 12 months of age. Our findings demonstrate early and progressive vocal deficits in the TgF344-AD rat model. We further provide evidence of dysregulation of AD-pathology-related genes as well as inflammatory genes in the TA muscles of TgF344-AD rats in the early stage of the disease, confirming this rat model for early-stage investigations of voice deficits and related pathology.
Description of the data, software, and file structure
We have uploaded a text document containing the full statistical breakdown of the data from the USV analysis of the animal’s calls (PER_CT.txt), Analyzed USV data and its statistics (ADCohort2USVsForGlen_Krasko_V2.xlsx), Gene expression data and its statistics (AD_pilot-Gene_Expression_Results-_Bar_Chart.xlsx), R file containing added output for gene analysis(biorad.r), Gene expression output from the Bio-Rad PCR machine (AD_pilot.mgxd)
Abbreviations
FM- Frequency Modulated.
WT- Wild-type.
AD- Alzheimer’s Disease.
SD- Standard Deviation
USV- Ultrasonic Vocalization
N/A- Not applicable, used to fill cells that were missing/had no data for that cell.
Software_Descriptions
MatLab- Program used to run DeepSqueak for USV analysis.
DeepSqueak- Program used to detect, analyze, and characterize USV call files, used to export the analyzed data for statistical analysis.
File_Desctription
1)ADCohort2_USVs_v2.xlsx
a)NumberofUSVs
Genotype
TgF344-AD- Knockout rat model used to show AD symptoms similar to humans.
WT- Wild-type animal used as a control.
Animal.ID- A randomly assigned number used to identify an animal. Currently labeled N/A to de-identify the data.
Age- Animal ages in months when the data was collected.
Timepoint
Baseline- The initial timepoint, collected at the animal age of 6 months.
T2- Timepoint 2/Final, collected at the animal age of 9 months.
Label
Short- Duration less than 12ms; any call with 10ms or less duration.
Flat- Near constant frequency greater than 30kHz with a mean slope between -0.2 and 0.2 kHz/ms; Flat calls are mostly steady state frequencies longer than 10ms. They can have small frequency modulations <15kHz, short interruptions(<10ms), or two short calls.
Upward_Ramp- Monotonically increasing in frequency, with a mean slope not less than 0.2kHz/ms; should have >200kHz/s slope.
Downward_Ramp- Monotonically decreasing in frequency, with a mean negative slope not less than 0.2kHz/ms; Should have <-200kHz/ms slope.
Inverted_U- A monotonic increase followed by a monotonic frequency decrease, each of at least 5kHz; Need to have a rise and fall pattern.
Step_Up-Instantaneous frequency change to a higher frequency; Can be continuous or have short interruptions. Should not have a combination of inverted U’s.
Step_Down- Instantaneous frequency change to a lower frequency; Can be continuous or have short interruptions.
Multistep- Two or more instantaneous frequency changes; Should not have strong harmonics (if they do, it’s either a split or composite).
Complex- Containtwo or more directional changes in the frequency of at least 3kHz each; Calls should have a frequency modulation of 15kHz or greater.
Composite- Calls (other than flat/trill combinations) that comprise two or more categories; Calls are combinations of 2 calls except for Flat-Trill, 2-shorts, or flat-shorts (step-up, step-down, or flat depending on shape).
Trill- Rapid frequency oscillations with a period of approximately 15ms (either sinusoidalor appearing as repeated “inverted U’s”).
Flat_Trill_Combination- A trill that is flanked on one or both sides by a monotonic portion that is no less than 10ms; Are flat, ramp down, or ramp up + trill. The U’s on the trill do not need to be symmetrical.
Trill_with_Jumps- A trill that contains one or more higher-frequency components; Are typically not seen in our data.
Split- Middle component “jumps” to a lower frequency and contains a harmonic; Calls must have a strong harmonic component.
Assignment- The group was the animal assigned to.
Date- The day when the data was collected.
Count- Call count.
b)Master
Cohort- The cohort the animal was assigned to.
Assignment- designates the animal by which group it was assigned
Timepoint
Baseline- The initial timepoint, collected at the animal age of 6 months.
T2- Timepoint 2/Final, collected at the animal age of 9 months.
Age- Animal ages in months when the data was collected.
Date- The day when the data was collected.
Genotype
TgF344-AD- Knockout rat model used to show AD symptoms similar to humans.
WT- Wild-type animal used as a control.
File- Internal location of where the corresponding file was saved. Labeled N/A as this column was used for internal tracking only.
Animal.ID- A randomly assigned number used to identify an animal. Relabeled to N/A to de-identify the data.
Label
Short- Duration less than 12ms; any call with 10ms or less duration.
Flat- Near constant frequency greater than 30kHz with a mean slope between -0.2 and 0.2 kHz/ms; Flat calls are mostly steady state frequencies longer than 10ms. They can have small frequency modulations <15kHz, short interruptions(<10ms), or two short calls.
Upward_Ramp- Monotonically increasing in frequency, with a mean slope not less than 0.2kHz/ms; should have >200kHz/s slope.
Downward_Ramp- Monotonically decreasing in frequency, with a mean negative slope not less than 0.2kHz/ms; Should have <-200kHz/ms slope.
Inverted_U- A monotonic increase followed by a monotonic frequency decrease, each of at least 5kHz; Need to have a rise and fall pattern.
Step_Up-Instantaneous frequency change to a higher frequency; Can be continuous or have short interruptions. Should not have a combination of inverted U’s.
Step_Down- Instantaneous frequency change to a lower frequency; Can be continuous or have short interruptions.
Multistep- Two or more instantaneous frequency changes; Should not have strong harmonics (if they do, it’s either a split or composite).
Complex- Containtwo or more directional changes in the frequency of at least 3kHz each; Calls should have a frequency modulation of 15kHz or greater.
Composite- Calls (other than flat/trill combinations) that comprise two or more categories; Calls are combinations of 2 calls except for Flat-Trill, 2-shorts, or flat-shorts (step-up, step-down, or flat depending on shape).
Trill- Rapid frequency oscillations with a period of approximately 15ms (either sinusoidalor appearing as repeated “inverted U’s”).
Flat_Trill_Combination- A trill that is flanked on one or both sides by a monotonic portion that is no less than 10ms; Are flat, ramp down, or ramp up + trill. The U’s on the trill do not need to be symmetrical.
Trill_with_Jumps- A trill that contains one or more higher-frequency components; Are typically not seen in our data.
Split- Middle component “jumps” to a lower frequency and contains a harmonic; Calls must have a strong harmonic component.
Accepted- Subjective decision made based on the contour strength of a call. A call is rejected if the contour is too weak/ doesn’t match the call. Measured as either True if accepted or False if rejected.
Score- A number assigned by DeepSqueak Rating score.
Begin.Time- Time a call started, measured in milliseconds (ms).
End.Time- Time a call ended, measured in milliseconds (ms).
Call.Length- Time duration of a call, measured in milliseconds (ms).
Principle.Frequency- Median frequency of the frequencies within the call contour, Measured in kilohertz (kHz).
Low.Freq- Measure of minimum and frequency of the call contour, measured in kilohertz (kHz).
High.Freq- Measure of maximum and frequency of the call contour, measured in kilohertz (kHz).
Delta.Freq- The difference between the maximum and minimum call frequencies (Bandwidth), measured in kilohertz (kHz).
Frequency.Standard.Deviation- SD of the call, measured in kilohertz (kHz).
Slope- Slope of the call, measured in kilohertz per second (kHz/s).
Sinuosity- Call contour path length divided by the distance between the start and end of the call.
Mean.Power- Average power spectral density of the call contour without background noise influences, measured in decibels per hertz (dB/Hz).
Tonality- Signal/Noise Ratio calculated by dividing the geometric mean of the power spectrum by the arithmetic mean and subtracting from 1
Peak.Freq-
c)USVParameters
Genotype
TgF344-AD- Knockout rat model used to show AD symptoms similar to humans.
WT- Wild-type animal used as a control.
Label
Short- Duration less than 12ms; any call with 10ms or less duration.
Flat- Near constant frequency greater than 30kHz with a mean slope between -0.2 and 0.2 kHz/ms; Flat calls are mostly steady state frequencies longer than 10ms. They can have small frequency modulations <15kHz, short interruptions(<10ms), or two short calls.
Upward_Ramp- Monotonically increasing in frequency, with a mean slope not less than 0.2kHz/ms; should have >200kHz/s slope.
Downward_Ramp- Monotonically decreasing in frequency, with a mean negative slope not less than 0.2kHz/ms; Should have <-200kHz/ms slope.
Inverted_U- A monotonic increase followed by a monotonic frequency decrease, each of at least 5kHz; Need to have a rise and fall pattern.
Step_Up-Instantaneous frequency change to a higher frequency; Can be continuous or have short interruptions. Should not have a combination of inverted U’s.
Step_Down- Instantaneous frequency change to a lower frequency; Can be continuous or have short interruptions.
Multistep- Two or more instantaneous frequency changes; Should not have strong harmonics (if they do, it’s either a split or composite).
Complex- Containtwo or more directional changes in the frequency of at least 3kHz each; Calls should have a frequency modulation of 15kHz or greater.
Composite- Calls (other than flat/trill combinations) that comprise two or more categories; Calls are combinations of 2 calls except for Flat-Trill, 2-shorts, or flat-shorts (step-up, step-down, or flat depending on shape).
Trill- Rapid frequency oscillations with a period of approximately 15ms (either sinusoidalor appearing as repeated “inverted U’s”).
Flat_Trill_Combination- A trill that is flanked on one or both sides by a monotonic portion that is no less than 10ms; Are flat, ramp down, or ramp up + trill. The U’s on the trill do not need to be symmetrical.
Trill_with_Jumps- A trill that contains one or more higher-frequency components; Are typically not seen in our data.
Split- Middle component “jumps” to a lower frequency and contains a harmonic; Calls must have a strong harmonic component.
Animal.ID- A randomly assigned number used to identify an animal. Relabeled to N/A to de-identify the data.
Date- Date the data was collected.
Assignment- Group the animal was assigned to.
Age- Age in months of the animal when the data was collected.
Timepoint
Baseline- The initial timepoint, collected at the animal age of 6 months.
T2- Timepoint 2/Final, collected at the animal age of 9 months.
Principle.Frequency.mean- The mean of the median frequency of the frequencies within the contour measured in Kilohertz (kHz).
Low.Frequency.mean- The mean of the measure of the minimum and frequency of the call contour measured in Kilohertz (kHz).
High.Frequency.mean-The mean of the measure of the maximum and frequency of the call contour measured in Kilohertz (kHz).
Delta.Frequency.mean- The mean of the difference between the maximum and minimum call frequencies (Bandwidth) measured in Kilohertz (kHz).
Call.Length.mean- The mean of the time duration of a call measured in milliseconds (ms).
Mean.Power.mean- The mean of the average power spectral density of the call contour without background noise influences, measured in decibels per hertz (dB/Hz).
Slope.mean- The mean of the slope of the call measured in Kilohertz per second (kHz/s).
Peak.Freq.mean- The mean of the frequency at the greatest amplitude (highest power) within the call measured in Kilohertz (kHz).
d)Stats
Genotype
TgF344-AD- Knockout rat model used to show AD symptoms similar to humans.
WT- Wild-type animal used as a control.
Label
Simple- A call category that has a simple contour; contains the short, flat, upward ramp, downward ramp, inverted u, step up, and step down call characterizations.
FM- A call category that has a complex frequency-modulated contour; contains the multistep, complex, composite, trill, flat trill combination, and trill with jumps call characterizations.
Harmonic- A call category the has a harmonic contour; and contains the Split call characterization.
Animal.ID- A randomly assigned number used to identify an animal. Relabeled to N/A to de-identify the data.
Date- Date the data was collected.
Assignment- Group the animal was assigned.
Age- Animal age in months at the date the data was collected.
Timepoint
Baseline- The initial timepoint, collected at the animal age of 6 months.
T2- Timepoint 2/Final, collected at the animal age of 9 months.
Principle.Frequency.mean- The mean of the median frequency of the frequencies within the contour measured in Kilohertz (kHz).
Low.Freq.mean- The mean of the measure of the minimum and frequency of the call contour measured in Kilohertz (kHz).
High.Freq.mean- The mean of the measure of the maximum and frequency of the call contour measured in Kilohertz (kHz).
Call.Length.mean- The mean of the time duration of a call measured in milliseconds (ms).
Mean.Power.mean- The mean of the average power spectral density of the call contour without background noise influences, measured in decibels per hertz (dB/Hz).
Slope.mean- The mean of the slope of the call measured in Kilohertz per second (kHz/s).
Peak.Freq.mean- The mean of the frequency at the greatest amplitude (highest power) within the call measured in Kilohertz (kHz).
e)Fig1
Animal.ID- A randomly assigned number used to identify an animal. Relabeled to N/A to de-identify the data.
Age- Age in months of the animal when the data was collected.
Call.Length.mean- The mean of the time duration of a call measured in milliseconds (ms).
f)Fig2
Genotype
TgF344-AD- Knockout rat model used to show AD symptoms similar to humans.
WT- Wild-type animal used as a control.
Age- Age in months of the animal when the data was collected.
Call.Length.mean- The mean of the time duration of a call measured in milliseconds (ms).
g)Fig4
Genotype
TgF344-AD- Knockout rat model used to show AD symptoms similar to humans.
WT- Wild-type animal used as a control.
Age- Age in months of the animal when the data was collected.
Principal.Frequency.mean- The mean of the median frequency of the frequencies within the contour measured in Kilohertz (kHz).
h)Fig5
Genotype
TgF344-AD- Knockout rat model used to show AD symptoms similar to humans.
WT- Wild-type animal used as a control.
Age- Age in months of the animal when the data was collected.
Low.Frequency.mean- The mean of the measure of the minimum and frequency of the call contour measured in Kilohertz (kHz).
i)Fig6
Genotype
TgF344-AD- Knockout rat model used to show AD symptoms similar to humans.
WT- Wild-type animal used as a control.
Age- Age in months of the animal when the data was collected.
High.Freq.mean- The mean of the measure of the maximum and frequency of the call contour measured in Kilohertz (kHz).
j)Fig7
Genotype
TgF344-AD- Knockout rat model used to show AD symptoms similar to humans.
WT- Wild-type animal used as a control.
Slope.mean- The mean of the slope of the call measured in Kilohertz per second (kHz/s).
k)Fig9
Genotype
TgF344-AD- Knockout rat model used to show AD symptoms similar to humans.
WT- Wild-type animal used as a control.
Age- Age in months of the animal when the data was collected.
Mean.Power.mean- The mean of the average power spectral density of the call contour without background noise influences, measured in decibels per hertz (dB/Hz).
l)Fig10
Genotype
TgF244-AD- Knockout rat model used to show AD symptoms similar to humans.
WT- Wild-type animal used as a control.
Age- Age in months of the animal when the data was collected.
Mean.Power.mean- The mean of the average power spectral density of the call contour without background noise influences, measured in decibels per hertz (dB/Hz).
m)Fig12
Genotype
TgF344-AD- Knockout rat model used to show AD symptoms similar to humans.
WT- Wild-type animal used as a control.
Age- Age in months of the animal when the data was collected.
Peak.Freq.mean- The mean of the frequency at the greatest amplitude (highest power) within the call measured in Kilohertz (kHz).
n)fig13
Genotype
TgF344-AD- Knockout rat model used to show AD symptoms similar to humans.
WT- Wild-type animal used as a control.
Age- Age in months of the animal when the data was collected.
Peak.Freq.mean- The mean of the frequency at the greatest amplitude (highest power) within call measured in Kilohertz (kHz).
2)AD_pilot-Gene_Expression_Results-Bar_Chart.xlsx
Target
Bace2- Beta-secretase 2.
Chat- Choline Acetyltransferase.
CTSL- Cathepsin L1.
Foxp3- Forkhead Box Protein P3.
Hsp- Heat Shock Protein.
IFNA1- Alpha Interferon.
IFNgamma- Interferon Gamma.
Igf2- Insulin-like Growth Factor.
IL10- Interleukin 10.
IL12- Interleukin 12.
IL18- Interleukin 18.
IL1a- Interleukin 1 Alpha.
IL1b- Interleukin 1 Beta.
IL1r1- Interleukin 1 Receptor, Type 1.
IL2- Interleukin 2.
IL4- Interleukin 4.
Il6- Interleukin 6.
Jun- Transcription Factor Jun.
Myd88- Myeloid Differentiation Primary Response 88.
Pkp4- Plakophilin 4.
Prkcd- Protein Kinase, DNA-Activated, Catalytic Subunit.
PRKCg- Protein Kinase C Gamma Type.
Rorcx1,2- Retinoic Acid-Related Orphan Receptor C variant 1,2.
Rorcx3- Retinoic Acid-Related Orphan Receptor C variant 3.
Serpina- Serine Protease Inhibitors.
TNFa- Tumor Necrosis Factor Alpha.
Uqcrc2- Cytochrome b-c1 complex subunit 2, mitochondrial.
Biological_Group
ADTg- TgF344-AD knockout rat model was used to show AD symptoms similar to humans.
WT- Wild-type animal used as a control.
Control- Control for gene expression.
Expression- Relative normalized expression in fold change.
Exp_Lower_Error_Bar- the lower range on the error bar for the expression value.
Exp_Upper_Error_Bar- the upper range on the error bar for the expression value.
P-value- the statistical value showing the significance of the collected data.
3)Per_CT.txt- A text document containing all of the statistical analysis done using the gathered data in both ADCohort2_USVs_v2 and AD_pilot-Gene_Expression_Results-Bar_Chart.
4)AD_pilot.mgxd- Data file output from the Bio-Rad PCR machine outputs after the PCR plate is read.
5)biorad.r- R file that contains additional statistical analysis.
6)AD_pilot_image.bmp- An image showing what the .mgxd file contains for those who are unable to open it.
2.1 TgF344-AD rats
All work involving rats was approved by the University of Wisconsin-Madison School of Medicine and Public Health Institutional Animal Care and Use Committee (IACUC) and was conducted in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals (The National Academies Press, 2011).
Male TgF344-AD rats (n = 19) and male wildtype Fischer 344 (WT) rats (n = 19) arrived from the Rat Resource & Research Center (MO, United States) in 5 different age groups, and were housed in the same genotype pairs on a reverse light–dark-cycle (12:12 hours) to allow for testing during the active cycle, with full access to food and water ad libitum, as well as standard rodent enrichment (Bigelow et al., 2022). All rats were assigned to testing groups based on their date of birth and testing occurred at 6 and 9 months of age accordingly. The male test rats in this study were sexually naïve at the start of the study. Sexually mature female Long-Evans rats (n = 8; average age at testing timepoint 1: 3.67 months, SD: 1.75 months; Envigo Research Labs, PA, United States) were used as a stimulus to elicit vocalizations from the male test rats.
Prior to acclimation to USV collection, all rats were habituated to handling and transportation from the vivarium to the testing room for at least 30 minutes on 3 consecutive days. Acclimation to the testing procedure at each time point was performed for 5 days with a one-day break prior to recording. Behavioral acclimation and testing sessions were performed with start times ranging from 9 a.m. to mid-afternoon, under red lighting. To reduce risks for unconscious bias, rats were identified through alphanumeric code numbers, and researchers handling rats, conducting experiments, and analyzing data were blinded to genotype information.
2.2 Ultrasonic vocalizations
For vocalization testing, an ultrasonic microphone with 16-bit resolution and a sampling rate of 250 kHz (CM16, Avisoft Bioacoustics, Berlin, Germany) attached to an ultrasonic recording system (Avisoft Bioacoustics, Berlin, Germany) was mounted 15 cm above a standard polycarbonate rat home cage to record calls for analysis. Rats were placed in their home cage without their housing mate. Testing rat calls were elicited by introducing a sexually receptive stimulus female rat into the home cage of the experimental rat. Estrus was confirmed by observing a combination of behavioral signs (e.g., lordosis, ear wiggling, hopping, and darting) (Bialy et al., 2000; Brudzynski, 2021). The stimulus female rat was removed after either 2 mounts by the male rat or following signs of interest and prolonged approach behaviors during the initiation stage (i.e., chasing the female rat, sniffing, genital autogrooming). The recording was started once the stimulus rat was removed and male-only calls were recorded for 5 min. This mating paradigm has been described in previous work (Ciucci et al., 2010; Basken et al., 2012; Johnson et al., 2013; Hoffmeister et al., 2022; Broadfoot et al., 2023; Cullins et al., 2023). All rats in both genotypes displayed a variety of expected behaviors (i.e., exploration and autogrooming) after removal of the stimulus rat, and displayed a variety of call types.
Using DeepSqueak software (Coffey, United States), USVs were analyzed for low and high frequency in kHz (as a measure of minimum and maximum frequency of the call contour), peak frequency in kHz (frequency at the greatest amplitude within a call), principal frequency in kHz (median frequency of the frequencies within the call contour), call length (ms), and mean power in dB/Hz (average power spectral density of the call contour without background noise influences) as a measure of call intensity (Coffey et al., 2019). Calls were manually labeled into 16 call types as previously described by Wright et al. (2010).
As shown in Table 1, call types were later collapsed into simple, frequency modulated (FM), and harmonic call categories with short, flat, upward and downward ramp, inverted u, step up and step down calls denoting simple calls; multistep, complex, composite, trill, flat trill combination, and trill with jump calls were marked as frequency modulated (complex) calls; split calls were defined as harmonics, to ensure adequate number of calls for statistical analyses. The number of calls per rat and call type was determined and the ratio of complex calls was calculated in % complex (FM, harmonic calls). Ultrasonic vocalizations were collected at 6 months (baseline) and at 9 months of age (early stage) on 3 consecutive days. The day of best performance, based on the total number of calls, was used for each rat for further statistical analysis, described below.
2.3 Inflammation in the TA muscle
Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to assay peripheral inflammation and AD-related pathology in the TA muscle. MIQE guidelines were followed in our protocol to ensure the reliability and reproducibility of our results (Bustin et al., 2009). Because the testing rats were scheduled to undergo additional testing procedures, we used tissue samples from our separate pilot cohort [male TgF344-AD rats (n = 6) and male Fischer-344 WT rats (n = 6)], which were harvested at the final 12-month timepoint to characterize peripheral inflammation and AD pathology. All available pilot rats underwent a similar ultrasonic vocalization protocol to the one described.
One hemilarynx of random laterality from each animal was rapidly dissected following decapitation, frozen in Tissue-Tek Optimal Cutting Temperature Compound (Sakura Finetek, Tokyo, Japan) under liquid nitrogen, and stored at −80°C until further processing. Hemilarynges were then dissected (TA muscles) on wet ice under a dissecting microscope, rinsed in ice-cold PBS, and frozen on dry ice until RNA extraction.
Total RNA was extracted from TA muscles using an RNeasy Fibrous Tissue Mini Kit (QIAGEN, Hilden, Germany). RNA quality and concentration were quantified using a NanoDrop ND-1000 UV–Vis spectrophotometer (Thermo Scientific, Waltham, Massachusetts, United States). Three samples with the highest quality and concentration of RNA were chosen from each group (WT: n = 3, TgF344-AD: n = 3). iScript Reverse Transcription Supermix for RT-qPCR (Bio-Rad, Hercules, California, United States) generated cDNA from each sample using 750 ng in addition to no template and no reverse transcriptase negative control reactions.
Primers to genes of interest were designed using Primer-BLAST (National Center for Biotechnology Information, NIH) with ideal annealing temperature at 60°C, spanning an exon-exon junction, and without nonspecific targets (Table 2). Primers were ordered from Integrated DNA Technologies (IDT, Coralville, Iowa, United States). Due to the limited retrievable quantities of RNA from the TA muscle and low expected concentrations of several target mRNAs, samples were first preamplified with SsoAdvanced PreAmp Supermix (Bio-Rad, Hercules, California, United States) using a multi-primer assay cocktail. Following preamplification, reactions were diluted 1:20 in TE buffer except for a pooled sample of cDNA that was diluted 1:5 in TE buffer and used to generate standard curves after 1:10 serial dilution.
RT-qPCR with SsoFast EvaGreen supermix (Bio-Rad, Hercules, California, USA) was used with forward and reverse primer final concentrations of 500 nM. 1 μL cDNA was used in each reaction, and all reactions were run in triplicate with a no template and a no reverse transcriptase negative control on each plate. PCR reactions were run and analyzed in the CFX Opus 96 RT-PCR System and CFX Maestro software (Bio-Rad, Hercules, California, USA). Cycle parameters were per supermix protocol with Tanneal = 60°C melt curve analysis following amplification. Assays shown had PCR reaction efficiencies from 90 to 110%, R2 > 0.98, and a single product on melt curve analysis. All individual primer assays were run on the same plate with standard curves and values were normalized to the Hsp90 housekeeping gene (Pfaffl, 2001).
2.4 Statistical analyses
2.4.1 Ultrasonic vocalizations
SAS 9.4 (SAS Institute, Inc., Cary, NC) was used for all statistical analyses. A repeated-measures two-way ANOVA, with genotype (TgF344-AD, WT) and age (6 months, 9 months) as independent variables (each rat was considered the experimental unit) for each call category (simple, FM, harmonic) was used to assess all dependent variables associated with ultrasonic vocalizations (duration, low frequency, high frequency, peak frequency, principal frequency, mean power). All rats were tested at baseline/6 months (N = 38; WT: n = 19, TgF344-AD: n = 19). A subset of rats were aged up to the 9-month timepoint (N = 18; WT: n = 10, TgF344-AD: n = 8). The number of calls was collected per call type, collapsed into call categories (simple, FM, harmonic), and the number of complex calls was calculated as a %-ratio. Post-hoc analysis was completed using a Tukey–Kramer adjustment. The critical level for significance was set at α < 0.05.
2.4.2 RT-qPCR
All reactions were normalized to the Hsp90 housekeeping gene. A Student’s t-test was run on the means of WT (n = 3) and AD samples (n = 3). The critical level for significance was set at α < 0.05. Analysis was performed on Bio-Rad CFX Maestro software which accounts for differential reaction efficiencies based on Pfaffl (2001). Cohen’s d effect size was calculated using G*Power 3.1.9.7 (Erdfelder, Faul, & Buchner, Düsseldorf, Germany) (Faul et al., 2007).