Introduction
Lysosomal membrane stability (LMS – membrane permeability and proton pump function) in marine fish, molluscs and earthworms has been widely used in environmental assessments (Moore et al., Reference Moore, Allen and McVeigh2006a, Reference Moore, Allen, McVeigh and Shaw2006b; Holth et al., Reference Holth, Beckius, Zorita, Cajaraville and Hylland2011; Sforzini et al., Reference Sforzini, Dagnino, Oliveri, Canesi and Viarengo2011; Martínez-Gómez et al., Reference Martínez-Gómez, Bignell and Lowe2015; Pantea et al., Reference Pantea, Coatu, Damir, Oros, Lazar and Rosoiu2023; Soms-Molina et al., Reference Soms-Molina, Martínez-Gómez, Zuñiga, Rodilla and Falco2024; Itziou, Reference Itziou2025). Various environmental factors have been considered as contributing to measurement of LMS; however, the relationship between LMS and the age of the animals has not been generally considered in these studies.
Age-related dysfunctional changes in lysosomes and autophagy have been demonstrated in various animal species, including humans (Cuervo, Reference Cuervo2004, Reference Cuervo2008; Numan et al., Reference Numan, Brown and Michou2015; Guerrero-Navarro et al., Reference Guerrero-Navarro, Jansen-Dürr and Cavinato2022). Marine mussels Mytilus edulis (L.) showed an age-related decline in their ability for lysosomal function to recover following stress from hypoxia and copper induced toxicity (Hole et al., Reference Hole, Moore and Bellamy1993, Reference Hole, Moore and Bellamy1995). Mussels are also known to have a reduction in fecundity and embryonic viability with increasing age (Sukhotin and Flyachinskaya, Reference Sukhotin and Flyachinskaya2009).
LMS (i.e., membrane permeability), endocytosis, phagocytosis, and augmented autophagy are regulated by the cell signalling serine kinase known as the mechanistic target of rapapmycin, mTOR (specifically – PI3K/Akt/mTORC1), although mTORC2 also plays a role in regulating autophagy (Laplante and Sabatini, Reference Laplante and Sabatini2012; Sforzini et al., Reference Sforzini, Moore, Oliveri, Volta, Jha, Banni and Viarengo2018; Ballesteros-Álvarez and Andersen, Reference Ballesteros-Álvarez and Andersen2021; Raghuvanshi et al., Reference Raghuvanshi, Raghuvanshi, Kumar, Nepovimova, Valko, Kuca and Verma2025). In mammalian cells, both lysosomal function and basal autophagy are known to decline with increasing age, which can contribute to cell senescence and cell death. mTORC1 is primarily a nutrient sensor, however, it also interacts with ROS (Mitchell et al., Reference Mitchell, Madrigal-Matute, Scheibye-Knudsen, Fang, Aon, González-Reyes, Cortassa, Kaushik, Gonzalez-Freire, Patel and Wahl2016; Guerrero-Navarro et al., Reference Guerrero-Navarro, Jansen-Dürr and Cavinato2022). Overall, autophagy plays an essential role in the overall homeostasis of the cell (Cuervo, Reference Cuervo2004, Reference Cuervo2008; Yen and Klionsky, Reference Yen and Klionsky2008; Moore et al., Reference Moore, Shaw, Pascoe, Beesley, Viarengo and Lowe2020). Furthermore, previous studies have demonstrated that LMS in these cells is an effective measure of whole animal health status (Moore et al., Reference Moore, Koehler, Lowe, Viarengo and Klionsky2008; Sforzini et al., Reference Sforzini, Moore, Oliveri, Volta, Jha, Banni and Viarengo2018, Reference Sforzini, Oliveri, Barranger, Jha, Banni, Moore and Viarengo2020).
Autophagy is a cellular waste removal and recycling process that is activated in response to various types of metabolic stress and including nutrient deprivation, as well as exposure to toxic metals and xenobiotics causing generation of ROS, growth factor depletion, and hypoxia (Cuervo, Reference Cuervo2004, Reference Cuervo2008; Moore, Reference Moore2004; Yen and Klionsky, Reference Yen and Klionsky2008).
This investigation was designed to assess lysosomal function, autophagy, and intra-lysosomal ROS generation in a molluscan model, namely, the digestive gland or hepatopancreatic digestive tubule epithelial cells (i.e., digestive cells) and blood cells (i.e., haemocytes) of the marine mussel Mytilus edulis from three age groups (i.e., 2-4 years, 5-6 years, and ≥ 10 years).
Materials and methods
Animal collection and acclimation
Mussels (Mytilus edulis) of three age categories (2-4 years [2.9-4.6 cm shell length]; 5-6 years [5.2–5.8 cm shell length]; and ≥ 10 years [≥7 cm shell length]), were collected from Beggar’s Island in the River Lynher/Tamar Estuary near Plymouth (ambient seawater temperature at time of collection was 15°C; UK – Grid Reference: SX 42363 57187). Mussels were selected on the basis of a von Bertalanffy growth curve (a revised version of the curve by Bayne and Worrall, Reference Bayne and Worrall1980) relating shell length to age for this population (Fig. 1; Hole et al., Reference Hole, Moore and Bellamy1993, Reference Hole, Moore and Bellamy1995). The mussels were cleaned of epiphytes and epizoites and acclimated for a minimum of 7 days in 20 l polypropylene tanks through which aerated, filtered, recirculating seawater flowed continuously (15° ± 1°C and 34 ± l%0 salinity). They were fed continuously on the alga Phaeodactylum tricornutum during the acclimation period (>30 mg dry weight algae/mussel/day based on a 5–6 year mussel) and maintained with a natural photoperiod.
Figure 1. Von Bertalanffy growth curve (a revised version of the curve) relating shell length to age for mussels (Mytilus edulis) from the estuary of the River Lynher/Tamar (Mean values ± 95% Confidence Limits). Adapted from Bayne and Worrall (Reference Bayne and Worrall1980); and Hole et al. (Reference Hole, Moore and Bellamy1993, Reference Hole, Moore and Bellamy1995).
Eight mussels from each age group were randomly selected for the biomarker tests; all LMS and autophagy biomarker tests were applied to the same individual animals. ROS assessments used separate age-related samples of mussels.
Digestive cell preparation
Individual digestive glands were cut into small pieces (approx. 2 mm cubes) and incubated for 20 minutes at 15°C, with continuous agitation, in 125 ml trypsinising flasks containing 30 ml of Ca2+/Mg2+ free (CMFS) saline (20 mM HEPES, 500 mM NaCl, 12.5 mM KCl, 5 mM EDTA, gassed for 10 min with 95% 02:5% CO2 and adjusted to pH 7.3 with 1 N NaOH (Peek and Gabbott, Reference Peek and Gabbott1989). Following the pre-treatment with the CMFS, trypsin (Sigma-Aldrich T8642) was added to the solution (12.5 mg/30 ml) and the agitation continued for a further 20 min at 15°C. The resulting cell solution was then filtered through 100 µm gauze and the cells were spun down in a refrigerated (10°C) centrifuge at 200 g for 10 minutes. Following centrifugation, the resulting cell pellet was re-suspended in fresh CMFS, centrifuged once again and the pellet re-suspended in RPMI1640 balanced salt solution (Dutch Modification) to which had been added 2.5% NaCl (w:v) and 10% NuSerum, as described by Lowe and Pipe (Reference Lowe and Pipe1994) and Lowe et al. (Reference Lowe, Soverchia and Moore1995, Reference Lowe, Moore and Readman2006).
Haemocyte preparation
Haemocytes were prepared as described by Lowe et al. (Reference Lowe, Soverchia and Moore1995): 100 µl of haemolymph was removed from the adductor muscle using a 1 ml hypodermic syringe with a 25 guage needle and containing 100 µl of physiological saline (0.02 M HEPES, 0.4 M NaCl, 0.1 M MgSO4, 0.01 M KCl, 0.01 M CaCl2, pH 7.3). The needle was then removed and the haemocyte suspension was transferred to 2 ml siliconised microcentrifuge tubes. Mussel haemocytes were allowed to attach to polylysine-coated glass microscope slides for subsequent LMS, autophagy and ROS assessment.
Neutral red (NR) & brilliant cresyl blue (BCB) lysosomal retention test
LMS was assessed in the digestive cells and haemocytes of mussels using the lysosomotropic probes neutral red (NR) and brilliant cresyl blue (BCB) (Sigma-Aldrich), essentially as described by Lowe and Pipe (Reference Lowe and Pipe1994) and Lowe et al. (Reference Lowe, Soverchia and Moore1995).
The test for each sample replicate was terminated when dye loss was evident in 50% (numerically assessed within each field of view) and the time recorded. The mean NR and BCB retention time was then calculated from the eight replicates.
Autophagy
Autophagy of fluorescently labeled cellular proteins using fluorescein isothiocyanate diacetate FITC-diacetate) was assessed as previously described (Moore et al., Reference Moore, Soverchia and Thomas1996, Reference Moore, Koehler, Lowe, Viarengo and Klionsky2008). The time required for evidence of vacuolar fluorescence in >50% of the cells observed in 10 different fields of microscopic view (approx. 200–400 cells) was taken as the end point for quantification of autophagic transfer of the FITC-labeled cytoplasmic proteins (Fig. 2A & B).
Figure 2. Confocal images of mussel haemocytes (2-4y) treated with FITC-diacetate showing: (A) even fluorescent labelling of cellular proteins after 30 minutes; (B) fluorescent vacuolar distribution of autophagocytosed FITC labelled proteins after a further 3 hours; (C) the distribution of fluorescent lysosomes in the same cell as B labelled with neutral red (rhodamine excitation); (D) merged images of B and C showing that lysosomes and vacuolar fluorescence are predominantly at the same sites (arrows). Scale bar = 10 µm. Adapted from Moore et al. (2009).
A laserscan confocal microscope (SARASTRO/Molecular Dynamics) with Silicon Graphics imaging capabilities was used in the detailed study of the localization of the fluorescent bioprobes.
To confirm that the FITC fluorescent vacuoles were in fact lysosomes, a separate set of haemocytes incubated, without coverslips, with FITC diacetate were further incubated with the fluorescent lysosomotropic probes neutral red and cresyl violet (both 10 μg/ml, fluorescence visualized using rhodamine excitation) (Fig. 2C & D; Rashid et al., Reference Rashid, Horobin and Williams1991; Lowe et al., Reference Lowe, Soverchia and Moore1995; Moore et al., Reference Moore, Soverchia and Thomas1996, Reference Moore, Koehler, Lowe, Viarengo and Klionsky2008; Sforzini et al., Reference Sforzini, Dagnino, Oliveri, Canesi and Viarengo2011).
Intra-lysosomal ROS
Digestive cells were incubated with the laser dye dihydrorhodamine (DHR) 123 (Invitrogen-Molecular Probes, Eugene, USA) (10 µM, 5 min). The reaction with ROS produces fluorescent rhodamine 123 and was quenched after 5 min by the addition of N-t-butyl-a-phenylnitrone (PBN) to give a final concentration of 100 mM (Winston et al., Reference Winston, Moore, Kirchin and Soverchia1991, Reference Winston, Moore, Straatsburg and Kirchin1996). Rhodamine 123 fluorescent images were captured digitally for later analysis (Sforzini et al., Reference Sforzini, Moore, Oliveri, Volta, Jha, Banni and Viarengo2018).
Fluorescent emission was measured against a set of graded images for the FITC emission in lysosomes, which were prepared using image analysis (Silicon Graphics). One hundred haemocytes were measured for ROS-induced fluorescence per age group.
Data analysis
The results of the cellular LMS and autophagy biomarkers in haemocytes and digestive cells were tested for significance using non-parametric univariate analysis (Mann–Whitney U-test) and non-parametric multivariate analysis software, PRIMER-Є v 6 (PRIMER-Є Ltd., University of Auckland, New Zealand; Clarke, Reference Clarke1999). ROS data were not included as these were assessed in digestive cells from separate age groups of mussels for logistical reasons.
Principal component analysis (PCA), cluster analysis, and non-metric multi-dimensional scaling analysis (MDS), derived from Euclidean distance similarity matrices was used to visualise dissimilarities between sample groups. All data were logn-transformed and scale standardised prior to analysis. The results were further tested for significance using analysis of similarity (ANOSIM, PRIMER-Є v 6), which is analogous to a univariate ANOVA and reflects on differences between treatment groups in contrast to differences among replicates within treatment groups (the R statistic).
Finally, the PRIMER-Є v6 – BIO-ENV routine linking multivariate biomarker response patterns was used to identify small subsets of ‘influential’ biomarkers capturing the full MDS biomarker response pattern.
Results
Neutral red (NR) & brilliant cresyl blue (BCB) lysosomal retention test
LMS determined using the lysosomotropic amphiphilic cationic molecular probes, NR and BCB (Rashid et al., Reference Rashid, Horobin and Williams1991), was significantly reduced in haemocytes and digestive cells in both the older age groups (Fig. 3A & B). Both NR and BCB probes gave similar results for LMS.
Autophagy
Lysosomal autophagy in the haemocytes was similar in the 2–4 year and 5–6 year age groups but was markedly reduced in the ≥10-year category of mussels (Fig. 3C). Most of the FITC-positive autophagic vacuoles also sequestered the lysosomotropic molecular probes neutral red (NR) and cresyl violet (CV) indicating that they were autophagolysosomes (Fig. 2B, C & D).
Figure 3. (A) Lysosomal membrane stability in three age categories of mussel haemocytes using neutral red retentinon time (NRR) and brilliant cresyl blue (BCBR); (B) Lysosomal membrane stability in three age categories of mussel hepatopancreatic digestive cells using neutral red retention time (NRR) and brilliant cresyl blue retention time (BCBR); (C) Autophagic rate (as % of mean autophagy endpoint time in 2-4 y mussels) in three age categories of mussel haemocytes; (D) Reacyive oxygen species in the lysosomes of three age categories of mussel hepatopancreatic digestive cells. * - p ≤ 0.05, Mann-Whitneu U-test: Mean values ± 95% Confidence Limits/Square Root 2.
Intra-lysosomal ROS
Rhodamine 123 fluorescence produced by ROS in the lysosomes of mussel digestive cells, was similar in the 2–4 year and 5–6 year age groups but was markedly reduced in the ≥ 10-year group (Fig. 3D).
Integrated non-parametric multivariate statistical analysis (MVA)
The four LMS biomarkers and autophagy were used to determine the health status of the cells: these were lysosomal neutral red retention time (NRR) and brilliant cresyl blue retention time (BCBR) in digestive cells and haemocytes (LMS & autophagy) as an integrative measure of general health status (Moore et al., Reference Moore, Koehler, Lowe, Viarengo and Klionsky2008). Results from a non-parametric rank correlation matrix (PRIMER-Є v6, Draftsman pairwise scatter plots) showed that the LMS (i.e., NRR and BCBR) results were strongly correlated in the haemocytes and digestive cells respectively (Spearman’s Rank Correlation Coefficient rs = 0.829 [haemocytes], P ≤ 0.001; and rs = 0.806, P ≤ 0.001 [digestive cells]).
ANOSIM analysis of similarity showed that the three age groups were significantly different from each other (Fig. 4; 2–4 years v 5–6 years, P ≤ 0.001; 2–4 years v ≥ 10 years, P ≤ 0.002; 5–6 years v ≥ 10 years, P ≤ 0.001); while PCA and multidimensional scaling (MDS graph not shown as essentially the same as the PCA plot) combined with cluster analysis also showed clear separation of the three groups in Euclidian Space (Fig. 4). The four LMS biomarkers were strongly correlated with the first principal component PC1 (i.e., Spearman’s Rank Correlation Coefficients: PC1 v NRR haemocytes rs = 0.797, P ≤ 0.001; PC1 v BCBR haemocytes rs = 0. 883, P ≤ 0.001; PC1 v NRR digestive cells rs = 0.728, p ≤ 0.001; PC1 v BCBR digestive cells rs = − 0.737, P ≤ 0.001). Autophagic rate, however, was not significantly correlated with PC1 (PC1 v autophagic rate haemocytes rs = 0.291, P > 0.05 [NS]), but was inversely correlated with the second principal component (PC2 v autophagic rate haemocytes rs = − 0.732, ≤ 0.001).
Figure 4. Combined plot of principal component analysis (PCA) and cluster analysis (blue & red contours for Euclidian Distance of 1.7 and 2.6 respectively) for the four lysosomal membrane stability (LMS) biomarkers and autophagy for the three age categories of mussels. The % variation of the data captured by the first principal component (PC1) and the second principal component (PC2) is shown in the box on the right of the graph. The healthy zone is indicated on the left side and the dysfunctional zone is shown on the right side of the graph. Vectors are shown for the various biomarkers (LMS - NRR and BCBR in haemocytes and digestive cells; Autophagy in haemocytes). ANOSIM test results are included in the diagram.
The PRIMER-Є v6 – BIO-ENV routine indicated that combinations of two biomarkers (i.e., LMS in haemocytes and digestive cells) had Spearman’s rank correlation coefficients of rs = 0.807 – rs = 0.845 (Table 1). A Spearman’s rank correlation coefficient rs = 0.7 (P ≤ 0.001) was used as the minimum significant threshold for reasonable interpretation of the data.
Table 1. BIO-ENV results for the combination of two influential biomarkers capturing the full MDS of the full LMS and autophagy biomarker response pattern
NRR – lysosomal neutral red retention time; BCBR – lysosomal brilliant cresyl blue retention time.
Discussion
The results showed that autophagy and lysosomal stability in the mussel haemocytes declined with age (Fig. 3A & C). Furthermore, LMS in the digestive cells of the digestive gland tubules declined with age with evidence of a greater decrease in the digestive cells (Fig. 3B). The digestive cells along with the gills are probably the main interface with the environment, particularly for contaminants associated with food particles (Moore et al., Reference Moore, Depledge, Readman and Leonard2004). ROS generation in the lysosomes of hepatopancreatic digestive cells was also reduced in the ≥ 10-year age category of mussels (Fig. 3D). Lysosomal function and autophagy are mechanistically linked so a decline in LMS will affect the acidic intra-lysosomal environment that is essential for degradation of macromolecules from endocytosed food and autophagocytosed intracellular constituents (Moore et al., Reference Moore, Sforzini, Viarengo, Barranger, Aminot, Readman, Khlobystov, Arnt, Banni and Jha2021). Failure to degrade these macromolecules and supra-molecular cell components will compromise the cellular nutritional system resulting in patho-physiological decline with age.
The finding that increased lysosomal and autophagic dysfunction with age in mussels agrees with previously observed effects that have been generally associated with ageing across many species and cell types (Cuervo, Reference Cuervo2008; Moore, Reference Moore2020; Guerrero-Navarro et al., Reference Guerrero-Navarro, Jansen-Dürr and Cavinato2022). The functional relationship between LMS and autophagy in mussels is well established, so we can reasonably assume that the age-related loss of LMS in digestive cells will indicate increased autophagic dysfunction in these cells as well as the haemocytes (Sforzini et al., Reference Sforzini, Moore, Oliveri, Volta, Jha, Banni and Viarengo2018, Reference Sforzini, Oliveri, Barranger, Jha, Banni, Moore and Viarengo2020). Such dysfunctional impairment will undoubtedly adversely affect the ability of the mussel digestive cells and haemocytes to degrade ingested materials by endocytosis and phagocytosis; and, also, to effectively recycle autophagocytosed cellular components. Furthermore, haemocytes are the immune cells providing innate immunity in mussels, mediated by phagocytosis and endocytosis, so age-related lysosomal dysfunction in these cells will potentially reduce their pathogen-killing ability (Canesi et al., Reference Canesi, Ciacci and Balbi2016).
The age-related decline in LMS and autophagy may be related in part to dysfunction of the PI3P-Akt-mTOR signalling pathway, as the mTOR signalling pathway is known to be an important node in the intricate web of ageing and its associated disorders (Fig. 5; Sforzini et al., Reference Sforzini, Moore, Oliveri, Volta, Jha, Banni and Viarengo2018; Moore et al., Reference Moore, Sforzini, Viarengo, Barranger, Aminot, Readman, Khlobystov, Arnt, Banni and Jha2021; Raghuvanshi et al., Reference Raghuvanshi, Raghuvanshi, Kumar, Nepovimova, Valko, Kuca and Verma2025). Lysosomal autophagy can also be a source of ROS generation as the degradation product of lysosomal digestion of lipoproteins is lipofuscin (age or stress pigment), which accumulates in autolysosomes and residual bodies (Brunk and Terman, Reference Brunk and Terman2002; Moore et al., Reference Moore, Viarengo, Donkin and Hawkins2007; Blagosklonny, Reference Blagosklonny2011; Filomeni et al., Reference Filomeni, De Zio and Cecconi2015). The relationship between mTOR and LMS and autophagy in mussels has been demonstrated previously by Sforzini et al. (Reference Sforzini, Oliveri, Barranger, Jha, Banni, Moore and Viarengo2020) and Moore et al. (Reference Moore, Sforzini, Viarengo, Barranger, Aminot, Readman, Khlobystov, Arnt, Banni and Jha2021), where mTOR (mTORC1) regulates autophagy and lysosomal membrane permeability (LMS) (Moore et al., Reference Moore, Sforzini, Viarengo, Barranger, Aminot, Readman, Khlobystov, Arnt, Banni and Jha2021). Furthermore, transcriptomic investigation of various cell physiological processes has indicated both increases and decreases in genes related to lysosomal function in mussels exposed to an environmental stressor (i.e., benzo[a]pyrene; Banni et al., Reference Banni, Sforzini, Arlt, Barranger, Dallas, Oliveri, Aminot, Readman, Moore, Viarengo and Jha2017).
Viarengo et al. (Reference Viarengo, Canesi, Pertica, Livigstone and Orunesu1991) indicated a significant increase in oxidative stress in older mussels, with the concentration of lipid peroxidation products (i.e., malondialdehyde) increased in old mussels (≥10 years old) with respect to younger animals. This finding indicated that an impairment of the antioxidant defence systems would render the older animals more susceptible to peroxidative stress, thus supporting the ‘“free radical theory of ageing’. However, this study only assessed ROS generation in the intra-lysosomal compartment of the digestive cells and this may reflect increased dysfunction in the lysosomes and in lysosomal autophagy.
The multivariate analysis demonstrated clear differences between the three age groups based on the six LMS biomarkers used in this investigation. PCA coupled with cluster analysis and ANOSIM indicated that there was an increase in lysosomal dysfunction with age thus supporting the findings of previous studies (Viarengo et al., Reference Viarengo, Canesi, Pertica, Livigstone and Orunesu1991; Hole et al., Reference Hole, Moore and Bellamy1993, Reference Hole, Moore and Bellamy1995). PCA has been shown previously to be a useful indicator of cellular homeostasis in mussels and earthworms; and it was strongly correlated with LMS (Sforzini et al., Reference Sforzini, Moore, Boeri, Bencivenga and Viarengo2015, Reference Sforzini, Moore, Oliveri, Volta, Jha, Banni and Viarengo2018; Moore et al., Reference Moore, Sforzini, Viarengo, Barranger, Aminot, Readman, Khlobystov, Arnt, Banni and Jha2021).
Figure 5. Diagramatic representatio of the cell physiological network for lysosomal and autophagic function. The nodes that are targets for age-related dysfunction are indicated in red. Dysfunction in the mTOR cell signalling system will probably affect endocytosis, phagocytosis, innate immunity (haemocytes) and growth.
LMS is a recognised indicator of organismal health and the reduction in this cell physiological parameter is indicative of a decrease in the homeostasis of the older mussels (Moore et al., Reference Moore, Sforzini, Viarengo, Barranger, Aminot, Readman, Khlobystov, Arnt, Banni and Jha2021). This factor will render the older animals more susceptible to environmental stressors such as increased seawater temperature, hypoxia, pathogen infections and chemical pollutants (Moore et al., Reference Moore, Viarengo, Donkin and Hawkins2007; Canesi et al., Reference Canesi, Ciacci and Balbi2016; Marigómez et al., Reference Marigómez, Múgica, Izagirre and Sokolova2017; Shaw et al., Reference Shaw, Moore, Readman, Mou, Langston, Lowe, Frickers, Al-Moosawi, Pascoe and Beesley2019). Augmented autophagy induced by caloric restriction and fasting have been proposed as having anti-ageing effects in a variety of animals (Cuervo, Reference Cuervo2008; Kitada and Koya, Reference Kitada and Koya2021). Fasting-induced autophagy in marine mussels and snails (periwinkles) has previously been shown to have anti-oxidative protective effects against environmental stressors including chemical pollutants (e.g., copper and polycyclic aromatic hydrocarbons); and these effects have also been simulated in a computational model of mussel digestive cells (McVeigh et al., Reference McVeigh, Allen, Moore, Dyke and Noble2004; Moore et al., Reference Moore, Shaw, Ferrar Adams and Viarengo2015, Reference Moore, Shaw, Pascoe, Beesley, Viarengo and Lowe2020).
Age-related effects on fecundity and population health are ecologically important considerations. The yolk granules in molluscan oocytes are lysosomes and accumulate organic xenobiotics as do the digestive cells (Moore et al., Reference Moore, Allen and McVeigh2006a). It is probably reasonable to expect the lysosomal yolk granules in oocytes to become increasingly dysfunctional with age as do the digestive cells and haemocytes. Consequently, lysosomal and autophagic dysfunction in the oocytes, together with the increased fragility in the health of older animals (e.g., digestion, autophagic recycling and repair, and immunity), has implications for fecundity and population health (Bayne et al., Reference Bayne, Salkeld and Worrall1983; Sukhotin and Flyachinskaya, Reference Sukhotin and Flyachinskaya2009). LMS in mussel digestive cells has been shown to be significantly correlated with ecological integrity (i.e., macrofaunal assemblage biodiversity) in a polluted Norwegian fjord (Moore et al., Reference Moore, Allen and Somerfield2006c). Furthermore, as mussels are an important foundation/keystone species in ecological assemblages (i.e., communities), the consequences for ecological integrity related to the age-structure of natural mussel populations, although mussels reared by aquaculture are harvested at a maximum of 2 years (https://www.msfoma.org › page_id = 631).
Consequently, it is recommended that young mussels should be used in environmental biomonitoring that use lysosomal and autophagic biomarkers.
Finally, broader interest in ageing and the pathobiology of mammalian and human lysosomal and autophagic processes, lies in the age-related neurodegenerative diseases including Dementia with Lewey Bodies, Alzheimer’s Disease, Parkinson’s Disease, and Huntington’s Chorea (Yen and Klionsky, Reference Yen and Klionsky2008; Matus et al., Reference Matus, Castillo and Hetz2012; Mao and Franke, Reference Mao and Franke2013; Wang, Reference Wang2013; Menzies et al., Reference Menzies, Fleming and Rubinsztein2015; Numan et al., Reference Numan, Brown and Michou2015; Mane et al., Reference Mane, Gajare and Deshmukh2018; Moore, Reference Moore2020; Jellinger, Reference Jellinger2025). While these pathological conditions manifest differently, they all share one pathological similarity: these neurodegenerative diseases are characterized by excessive failed autophagic build-up of proteins and protein aggregates inside neurons leading to cell dysfunction due to lysosomal degradative failure, and disease (Menzies et al., Reference Menzies, Fleming and Rubinsztein2015). Consequently, the age-related failure of protein degradation pathways by lysosomal autophagy may play a very important role in the etiology of these diseases; and the current study confirms that age-related decline in lysosomal and autophagic function occurs in invertebrates, with the possibility that this type of patho-physiological change may be widespread in lower animals (Sarkis et al., Reference Sarkis, Ashcom, Hawdon and Jacobson1988; Mitchell et al., Reference Mitchell, Madrigal-Matute, Scheibye-Knudsen, Fang, Aon, González-Reyes, Cortassa, Kaushik, Gonzalez-Freire, Patel and Wahl2016; Guerrero-Navarro et al., Reference Guerrero-Navarro, Jansen-Dürr and Cavinato2022).
Acknowledgements
The author wants to express his thanks to Margaret Thomas and Claudia Soverchia for their invaluable technical assistance. This research was supported in part by a NATO grant (R.G. 0108/88) and the PREDICT 2 project jointly supported by the UK Department for Environment, Food and Rural Affairs (Defra, UK) (contract number AE1136) and the Natural Environment Research Council (NERC, a component of UK Research & Innovation, UKRI), both of which are gratefully acknowledged.
Funding
This research was supported in part by a NATO grant (R.G. 0108/88) and the PREDICT 2 project jointly supported by the UK Department for Environment, Food and Rural Affairs (Defra, UK) (contract number AE1136) and the Natural Environment Research Council (NERC, a component of UK Research & Innovation, UKRI).
Data availability
Data can be made available upon request.
Competing interest
There are no conflicts of interest.
Open access
