Sarah M. Zala

Male house mice ( Mus musculus ) emit ultrasonic vocalizations (USVs) during courtship and mating, which influence their copulatory success. Several studies have found that playbacks of male USVs attract females, though this response may depend on the presence of male scent, and one study suggested that females are more attracted to complex than simple USV types. We conducted three playback experiments with wild-derived female house mice to test these predictions. None of our results met our expectations: First, females were not more attracted to sequences of complex versus simple USVs. Second, females were also not more attracted to these syllables when compared to silence. Third, females showed no attraction towards more natural sequences containing simple and complex USVs compared to silence, even in the presence of male scent. Thus, we found no evidence that wild-derived female mice show approach behavior towards male USVs, regardless of their complexity or exposure to male olfactory stimuli. These findings raise questions about the repeatability and generalizability of playback studies in house mice and highlight the need for more studies aimed at determining the types of vocalizations and contexts under which mice do and do not show attraction or other responses to USVs.

Low-carbohydrate, high-fat ketogenic diets (KDs) are used for treating drug-resistant epilepsy, and other potential benefits, such as treating neurological disorders, metabolic syndrome, and cancer are being explored. In addition to these and other medical applications, KDs have also become popular for rapid weight-loss and enhancing athletic performance. However, the potential negative effects of exposing developing offspring to KDs during pregnancy (gestational KD) are poorly understood, and especially the long-term health consequences. In this study, we investigated the effects of a partial gestational KD administered during the second half of pregnancy and assessed the consequences on the offspring over their entire lifespan. We found that, compared to controls, a gestational KD significantly reduced dams’ litter size and litter mass and altered the litter sex ratio, reducing the proportion of female offspring, which also had lower body mass early in their life. In contrast, male offspring exposed to a gestational KD suffered a significantly reduced lifespan and a late-onset increase in body mass. We found no evidence that a KD diet influenced some adult offspring behaviors (locomotion, anxiety, depression, circadian rhythms, food and water consumption) or reproductive success. Our results with laboratory mice may not translate to human health, but nevertheless, they should raise concerns that even a partial maternal KD during pregnancy may have detrimental effects on offspring health and longevity.

Background: It has been suggested that the expression of males’ secondary sexual traits provides reliable indicators of their sperm traits, predicting positive correlations between pre- and post-copulatory traits (Fertility Indicator Hypothesis). Yet, it has also been suggested that males face life-history tradeoffs between investing into primary versus secondary sexual traits, predicting negative correlations (Sexual Allocation Tradeoff Hypothesis). These two hypotheses are not mutually exclusive when males’ sexual traits are condition-dependent and high-quality males are better able to invest into both pre- and post-copulatory traits than low-quality males. To test these hypotheses, we manipulated the genetic quality of wild-derived male house mice by experimental inbreeding and first tested whether inbreeding affects primary or secondary sexual traits (condition-dependent expression). We then tested whether pre- and post-copulatory traits are correlated. We recorded courtship behavior and vocalizations of the males during female contact and measured males’ reproductive organs, sperm quality, and the expression of four genes associated with spermatogenesis. Results: Inbreeding did not reduce male courtship vocalizations, though it altered their vocal repertoire and reduced other courtship behaviors. Inbreeding negatively impacted relative testes mass and sperm quantity and quality, after two generations of inbreeding. We found no consistent correlations between pre-and post-copulatory traits, either positive or negative, regardless of inbreeding. Conclusions: Our results indicate that inbreeding impacted the expression of primary and secondary sexual traits in wild-derived house mice, which is the first such evidence to our knowledge, but we found no support for either the Fertility Indicator or the Sexual Allocation Tradeoff Hypotheses.

Low-carbohydrate, high-fat ketogenic diets (KDs) are used to treat drug-resistant epilepsy, and other potential benefits for treating neurological disorders, metabolic syndrome, and cancer are being explored. In addition to these and other medical applications, KDs have also become popular for rapid weight-loss and enhancing athletic performance. However, the effects of exposing developing offspring to KDs during pregnancy (gestational KD) are poorly understood, and especially their long-term health consequences. In this study, we investigated the effects of a partial gestational KD during the second half of pregnancy in mice and assessed the consequences on the offspring over their entire lifespan compared to offspring exposed to a control diet. We found that a gestational KD significantly reduced dams’ litter size and litter mass and altered the sex ratio at birth, reducing the proportion of female offspring, which also had lower body mass early in their life. In contrast, male offspring exposed to a gestational KD suffered a significantly reduced lifespan and a late-onset increase in body mass. We found no evidence that our KD diet influenced adult offspring behavior (locomotion, anxiety, depression, circadian rhythms, food and water consumption) or reproduction. These findings highlight the potential of even a partial maternal exposure to a KD to have surprisingly detrimental effects on offspring health and longevity, and thus raising concerns about its use during pregnancy.

Exposing female house mice (Mus musculus) to male urinary scent accelerates their sexual development (Vandenbergh effect). Here, we tested whether exposing juvenile male mice to females’ urine similarly influences male growth and size of their sexual organs. We exposed three-week old male house mice to female urine or water (control) for ca. three months. We found that female-exposed males grew significantly faster and gained more body mass than controls, despite all males being reared on a controlled diet, but we detected no differences in males' muscle mass or sexual organs. In contrast, exposing juvenile males to male urine had no effect their growth. We tested whether the males' accelerated growth imposed functional trade-offs on males' immune resistance to an experimental infection. We challenged the same male subjects with an avirulent bacterial pathogen (Salmonella enterica), but found no evidence that faster growth impacted their bacterial clearance, body mass or survival during infection compared to controls. Our results provide the first evidence to our knowledge that juvenile male mice accelerate their growth when exposed to the urine of adult females, though we found no evidence that increased growth had negative trade-offs on immune resistance to infectious disease.

House mice communicate through ultrasonic vocalizations (USVs), which are above the range of human hearing (>20 kHz), and several automated methods have been developed for USV detection and classification. Here we evaluate their advantages and disadvantages in a full, systematic comparison, while also presenting a new approach. This study aims to 1) determine the most efficient USV detection tool among the existing methods, and 2) develop a classification model that is more generalizable than existing methods. In both cases, we aim to minimize the user intervention required for processing new data. We compared the performance of four detection methods in an out-of-the-box approach, pretrained DeepSqueak detector, MUPET, USVSEG, and the Automatic Mouse Ultrasound Detector (A-MUD). We also compared these methods to human visual or ‘manual’ classification (ground truth) after assessing its reliability. A-MUD and USVSEG outperformed the other methods in terms of true positive rates using default and adjusted settings, respectively, and A-MUD outperformed USVSEG when false detection rates were also considered. For automating the classification of USVs, we developed BootSnap for supervised classification, which combines bootstrapping on Gammatone Spectrograms and Convolutional Neural Networks algorithms with Snapshot ensemble learning. It successfully classified calls into 12 types, including a new class of false positives that is useful for detection refinement. BootSnap outperformed the pretrained and retrained state-of-the-art tool, and thus it is more generalizable. BootSnap is freely available for scientific use.

House mice communicate through ultrasonic vocalizations (USVs), which are above the range of human hearing (>20 kHz), and several automated methods have been developed for USV detection and classification. Here we evaluate their advantages and disadvantages in a full, systematic comparison. We compared the performance of four detection methods, DeepSqueak (DSQ), MUPET, USVSEG, and the Automatic Mouse Ultrasound Detector (A-MUD). Moreover, we compared these to human-based manual detection (considered as ground truth), and evaluated the inter-observer reliability. All four methods had comparable rates of detection failure, though A-MUD outperformed the others in terms of true positive rates for recordings with low or high signal-to-noise ratios. We also did a systematic comparison of existing classification algorithms, where we found the need to develop a new method for automating the classification of USVs using supervised classification, bootstrapping on Gammatone Spectrograms, and Convolutional Neural Networks algorithms with Snapshot ensemble learning ( BootSnap ). It successfully classified calls into 12 types, including a new class of false positives used for detection refinement. BootSnap provides enhanced performance compared to state-of-the-art tools, it has an improved generalizability, and it is freely available for scientific use.