Biology subjects

Maillard, F.

Publications and source records attributed to Maillard, F..

5 recordsLinked to original sources

bioRxiv2026

pH-dependent anti-TfR1 NANOBODY(R) molecules deliver efficacious oligonucleotide payloads to muscle and CNS tissues

The blood-brain barrier (BBB) is a highly selective, semi-permeable border of endothelial cells that prevents solutes and therapeutic agents in systemic circulation from passively crossing into the central nervous system (CNS) parenchyma. The Transferrin receptor 1 (TfR1) endocytosis pathway for iron homeostasis is one of the most well-characterized strategies for therapeutic delivery across the BBB. The work presented here showcases the discovery of novel anti-TfR1 NANOBODY(R) shuttles. The identified anti-TfR1 NANOBODY(R) molecules display cross-reactivity and pH-dependent binding to human, cynomolgus (cyno), and mouse TfR1. Structural data further explain and support the underlying mechanism of this pH-dependent binding. These anti-TfR1 NANOBODY(R) molecules were successfully conjugated to both short-interfering RNA (siRNA) and antisense oligonucleotide (ASO) tool payloads. anti-TfR1 NANOBODY(R)-siRNA conjugates can induce up to 60% knockdown of the target mRNA transcript in skeletal muscle up to two weeks post a single IV dose in mice and up to 35-40% at four weeks post dose. Furthermore, extending the half-life of the anti-TfR1 NANOBODY(R)-ASO shuttles enhances heart, sciatic nerve, and brain exposure and enables up to 30-60% target knockdown in different CNS cell types. Altogether, these results highlight important features for the development of anti-TfR1 shuttles for the purpose of downregulating target mRNA transcripts in muscle and CNS for a variety of neurologic and neuromuscular indications.

neuroscience↗

bioRxiv2025

Experimental suppression of a keystone protist triggers mesopredator release and biotic homogenization in complex soil microbial communities

The keystone species concept suggests that certain members of an ecological community, despite their low abundance, exert disproportionately large effects on species diversity and composition. In microbial ecology, experimental validation of this concept is limited due to significant technical challenges associated with selective species manipulation. Here, we tested this concept within a soil microbial food web by selectively suppressing a protist predator using phototoxicity induced by excessive excitation light during fluorescence microscopy within a microfluidic soil chip system. We targeted a Hypotrichia ciliate taxon--presumed primarily bacterivorous under our experimental conditions--and combined microscopy with metabarcoding of multiple microbial trophic levels to evaluate the effects of this suppression on microbial community abundance, diversity, and composition. Over the 20-day incubation, the chip system supported complex communities of bacteria, fungi, and protists. Following Hypotrichia suppression, two distinct ecological responses were observed: first, an increase in flagellate abundance that was consistent with mesopredator release and accompanied a significant rise in overall protist diversity; second, a convergence in protist community composition, indicative of biotic homogenization. Surprisingly, bacterial community abundance, richness, and composition remained unaffected, likely due to compensatory predation by increased numbers of bacterivorous flagellates. In contrast, fungal diversity decreased following Hypotrichia suppression, presumably resulting from the altered protist communities that favored facultative fungal consumers. Collectively, these findings provide direct experimental evidence that low-abundance microbial predators can function as keystone species, modulating predator community composition and diversity and having cascading effects on lower trophic levels within the brown microbial food web.

ecology↗

bioRxiv2025

Warming and reduced rainfall alter fungal necromass decomposition rates and associated microbial community composition and functioning at a temperate-boreal forest ecotone

Changes in temperature and rainfall regimes will have significant yet potentially contrasting impacts on rates of soil organic matter (SOM) decomposition. To assess how a combined stress treatment of warming and drought impacts the decomposition of fungal necromass--a fast-cycling soil organic matter (SOM) pool--we incubated Hyaloscypha bicolor necromass under both ambient and altered conditions (air and soil warming +3.3{degrees}C and [~]40% reduced rainfall) at the B4Warmed experiment in Minnesota, USA. We conducted two multi-week incubations, one assessing mass loss and microbial community composition on decaying necromass after 1, 2, 7, and 14 weeks and the second characterizing the substrate utilization capacities of necromass- associated microbial communities after weeks 1 and 7. Warming and reduced rainfall significantly accelerated the initial rate of necromass decay by [~]20%, but overall mass loss was not different between treatments at the end of the 14-week incubation. The accelerated initial rate of decay paralleled shifts in microbial community composition and activity in the altered plots, demonstrating a higher metabolic capability to utilize C and N substrates early in decomposition but a lower capability later in decay. These findings highlight the dynamic, stage-dependent response of fungal necromass decomposition to altered climate regimes, underscoring the importance of considering both temporal dynamics and the functional capacity of microbial communities when assessing the impacts of climate change on soil carbon and nutrient cycling in forest ecosystems.

ecology↗

bioRxiv2024

Necromass chemistry interacts with soil mineral and microbial properties to determine fungal carbon and nitrogen persistence in soils

Despite the importance of mineral-associated organic matter (MAOM) in long-term soil carbon (C) and nitrogen (N) persistence, and the significant contribution of fungal necromass to this pool, the factors controlling the formation of fungal-derived MAOM remain unclear. This study investigated how fungal necromass chemistry, specifically melanin, interacts with soil mineral properties and microbial communities to influence MAOM formation and persistence. We cultured the fungus Hyaloscypha bicolor to produce {superscript 1}3C- and {superscript 1}{square}N-labeled necromass with varying melanin content (high or low) and incubated it in both live and sterile soils collected from six Indiana forests that differed in their clay and iron oxide (FeOx) content. After 38 days, we found that seven times more fungal-derived N was incorporated into MAOM than fungal-derived C, with fungal N comprising 20% of the MAOM-N pool. Low melanin necromass formed more MAOM-C than high melanin necromass, although site-level differences in overall MAOM formation were substantial. Soil clay and FeOx content were strong predictors of MAOM formation, explaining [~]60% and [~]68% of the variation in MAOM-C and MAOM-N, respectively. However, microbial communities significantly influenced MAOM formation, with MAOM-C formation enhanced and MAOM-N formation reduced in sterile soils. Furthermore, the relative abundance of fungal saprotrophs was negatively correlated, and bacterial richness was positively correlated with MAOM formation, and these relationships were influenced by necromass melanin content. This study reveals that microbial communities and soil properties interactively mediate the incorporation of fungal necromass C and N into MAOM, with microbes differentially influencing C and N incorporation, and these processes being further modulated by necromass melanization.

ecology↗

bioRxiv2023

Bacterial community characterization by deep learning aided image analysis in soil chips

Soil microbes play an important role in governing global processes such as carbon cycling, but it is challenging to study them embedded in their natural environment and at the single cell level due to the opaque nature of the soil. Nonetheless, progress has been achieved in recent years towards visualizing microbial activities and organo-mineral interaction at the pore scale, especially thanks to the development of microfluidic soil chips creating transparent soil model habitats. Image-based analyses come with new challenges as manual counting of bacteria in thousands of digital images taken from the soil chips is excessively time-consuming, while simple thresholding cannot be applied due to the background of soil minerals and debris. Here, we adopt the well-developed deep learning algorithm Mask-RCNN to quantitatively analyse the bacterial communities in soil samples from different locations in the world. This work demonstrates analysis of bacterial abundance from three contrasting locations (Greenland, Sweden and Kenya) using deep learning in microfluidic soil chips in order to characterize population and community dynamics. We additionally quantified cell- and colony morphology including cell size, shape and the cell aggregation level via calculation of the distance to the nearest neighbor. This approach allows for the first time an automated visual investigation of soil bacterial communities, and a crude biodiversity measure based on phenotypic cell morphology, which could become a valuable complement to molecular studies.

ecology↗