Direct identification of A-to-I editing sites with nanopore native RNA sequencing.

Inosine is a prevalent RNA modification in animals and is formed when an adenosine is deaminated by the ADAR family of enzymes. Traditionally, inosines are identified indirectly as variants from Illumina RNA-sequencing data because they are interpreted as guanosines by cellular machineries. However, this indirect method performs poorly in protein-coding regions where exons are typically short, in non-model organisms with sparsely annotated single-nucleotide polymorphisms, or in disease contexts where unknown DNA mutations are pervasive. Here, we show that Oxford Nanopore direct RNA sequencing can be used to identify inosine-containing sites in native transcriptomes with high accuracy. We trained convolutional neural network models to distinguish inosine from adenosine and guanosine, and to estimate the modification rate at each editing site. Furthermore, we demonstrated their utility on the transcriptomes of human, mouse and Xenopus. Our approach expands the toolkit for studying adenosine-to-inosine editing and can be further extended to investigate other RNA modifications.

MSC-Derived Small Extracellular Vesicles Exert Cardioprotective Effect Through Reducing VLCFAs and Apoptosis in Human Cardiac Organoid IRI Model.

Cardiovascular diseases (CVDs) are the leading cause of death worldwide, accounting for 31% of all deaths globally. Myocardial ischemia-reperfusion injury (IRI), a common complication of CVDs, is a major cause of mortality and morbidity. Studies have shown efficacious use of mesenchymal stem cells-derived small extracellular vesicles (MSCs-EVs) to mitigate IRI in animals, but few research has been done on human-related models. In this study, human embryonic stem cell-derived chambered cardiac organoid (CCO) was used as a model system to study the effects of MSC-EVs on myocardial IRI. The results revealed that MSC-EVs treatment reduced apoptosis and improved contraction resumption of the CCOs. Metabolomics analysis showed that this effect could be attributed to EVs' ability to prevent the accumulation of unsaturated very long-chain fatty acids (VLCFAs). This was corroborated when inhibition of fatty acid synthase, which was reported to reduce VLCFAs, produced a similar protective effect to EVs. Overall, this study uncovered the mechanistic role of MSC-EVs in mitigating IRI that involves preventing the accumulation of unsaturated VLCFA, decreasing cell death, and improving contraction resumption in CCOs.

Systematic Adaptation of Bacillus licheniformis to 2-Phenylethanol Stress.

The compound 2-phenylethanol (2-PE) is a bulk flavor and fragrance with a rose-like aroma that can be produced by microbial cell factories, but its cellular toxicity inhibits cellular growth and limits strain performance. Specifically, the microbe Bacillus licheniformis has shown a strong tolerance to 2-PE. Understanding these tolerance mechanisms is crucial for achieving the hyperproduction of 2-PE. In this report, the mechanisms of B. licheniformis DW2 resistance to 2-PE were studied by multi-omics technology coupled with physiological and molecular biological approaches. 2-PE induced reactive oxygen species formation and affected nucleic acid, ribosome, and cell wall synthesis. To manage 2-PE stress, the antioxidant and global stress response systems were activated; the repair system of proteins and homeostasis of the ion and osmotic were initiated. Furthermore, the tricarboxylic acid cycle and NADPH synthesis pathways were upregulated; correspondingly, scanning electron microscopy revealed that cell morphology was changed. These results provide deeper insights into the adaptive mechanisms of B. licheniformis to 2-PE and highlight the potential targets for genetic manipulation to enhance 2-PE resistance. IMPORTANCE The ability to tolerate organic solvents is essential for bacteria producing these chemicals with high titer, yield, and productivity. As exemplified by 2-PE, bioproduction of 2-PE represents a promising alternative to chemical synthesis and plant extraction approaches, but its toxicity hinders successful large-scale microbial production. Here, a multi-omics approach is employed to systematically study the mechanisms of B. licheniformis DW2 resistance to 2-PE. As a 2-PE-tolerant strain, B. licheniformis displays multifactorial mechanisms of 2-PE tolerance, including activating global stress response and repair systems, increasing NADPH supply, changing cell morphology and membrane composition, and remodeling metabolic pathways. The current work yields novel insights into the mechanisms of B. licheniformis resistance to 2-PE. This knowledge can also be used as a clue for improving bacterial performances to achieve industrial-scale production of 2-PE and potentially applied to the production of other relevant organic solvents, such as tyrosol and hydroxytyrosol.

Cottonseed Meal Protein Isolate as a New Source of Alternative Proteins: A Proteomics Perspective.

Cottonseed meal (CSM) is a good source of dietary proteins but is unsuitable for human consumption due to its gossypol content. To unlock its potential, we developed a protein extraction process with a gossypol removal treatment to generate CSM protein isolate (CSMPI) with ultra-low gossypol content. This process successfully reduced the free and total gossypol content to 4.8 ppm and 147.2 ppm, respectively, far below the US FDA limit. In addition, the functional characterisation of CSMPI revealed a better oil absorption capacity and water solubility than pea protein isolate. Proteome profiling showed that the treatment improved protein identification, while SDS-PAGE analysis indicated that the treatment did not induce protein degradation. Amino acid analysis revealed that post-treated CSMPI was rich in branched-chain amino acids (BCAAs). Mass spectrometry analysis of various protein fractions obtained from an in vitro digestibility assay helped to establish the digestibility profile of CSM proteins. Several potential allergens in CSMPI were also found using allergenic prediction software, but further evaluation based on their digestibility profiles and literature reviews suggests that the likelihood of CSMPI allergenicity remains low. Overall, our results help to navigate and direct the application of CSMPIs as alternative proteins toward nutritive human food application.

A synbiotic intervention modulates meta-omics signatures of gut redox potential and acidity in elective caesarean born infants.

BACKGROUND: The compromised gut microbiome that results from C-section birth has been hypothesized as a risk factor for the development of non-communicable diseases (NCD). In a double-blind randomized controlled study, 153 infants born by elective C-section received an infant formula supplemented with either synbiotic, prebiotics, or unsupplemented from birth until 4 months old. Vaginally born infants were included as a reference group. Stool samples were collected from day 3 till week 22. Multi-omics were deployed to investigate the impact of mode of delivery and nutrition on the development of the infant gut microbiome, and uncover putative biological mechanisms underlying the role of a compromised microbiome as a risk factor for NCD. RESULTS: As early as day 3, infants born vaginally presented a hypoxic and acidic gut environment characterized by an enrichment of strict anaerobes (Bifidobacteriaceae). Infants born by C-section presented the hallmark of a compromised microbiome driven by an enrichment of Enterobacteriaceae. This was associated with meta-omics signatures characteristic of a microbiome adapted to a more oxygen-rich gut environment, enriched with genes associated with reactive oxygen species metabolism and lipopolysaccharide biosynthesis, and depleted in genes involved in the metabolism of milk carbohydrates. The synbiotic formula modulated expression of microbial genes involved in (oligo)saccharide metabolism, which emulates the eco-physiological gut environment observed in vaginally born infants. The resulting hypoxic and acidic milieu prevented the establishment of a compromised microbiome. CONCLUSIONS: This study deciphers the putative functional hallmarks of a compromised microbiome acquired during C-section birth, and the impact of nutrition that may counteract disturbed microbiome development. TRIAL REGISTRATION: The study was registered in the Dutch Trial Register (Number: 2838 ) on 4th April 2011.

Multi-omics profiling of a CHO cell culture system unravels the effect of culture pH on cell growth, antibody titer, and product quality.

A robust monoclonal antibody (mAb) bioprocess requires physiological parameters such as temperature, pH, or dissolved oxygen to be well-controlled as even small variations in them could potentially impact the final product quality. For instance, pH substantially affects N-glycosylation, protein aggregation, and charge variant profiles, as well as mAb productivity. However, relatively less is known about how pH jointly influences product quality and titer. In this study, we investigated the effect of pH on culture performance, product titer, and quality profiles by applying longitudinal multi-omics profiling, including transcriptomics, proteomics, metabolomics, and glycomics, at three different culture pH set points. The subsequent systematic analysis of multi-omics data showed that pH set points differentially regulated various intracellular pathways including intracellular vesicular trafficking, cell cycle, and apoptosis, thereby resulting in differences in specific productivity, product titer, and quality profiles. In addition, a time-dependent variation in mAb N-glycosylation profiles, independent of pH, was identified to be mainly due to the accumulation of mAb proteins in the endoplasmic reticulum disrupting cellular homeostasis over culture time. Overall, this multi-omics-based study provides an in-depth understanding of the intracellular processes in mAb-producing CHO cell line under varied pH conditions, and could serve as a baseline for enabling the quality optimization and control of mAb production.

Nitro-Deficient Niclosamide Confers Reduced Genotoxicity and Retains Mitochondrial Uncoupling Activity for Cancer Therapy.

Niclosamide is an oral anthelmintic drug, approved for use against tapeworm infections. Recent studies suggest however that niclosamide may have broader clinical applications in cancers, spurring increased interest in the functions and mechanisms of niclosamide. Previously, we reported that niclosamide targets a metabolic vulnerability in p53-deficient tumours, providing a basis for patient stratification and personalised treatment strategies. In the present study, we functionally characterised the contribution of the aniline 4'-NO2 group on niclosamide to its cellular activities. We demonstrated that niclosamide induces genome-wide DNA damage that is mechanistically uncoupled from its antitumour effects mediated through mitochondrial uncoupling. Elimination of the nitro group in ND-Nic analogue significantly reduced γH2AX signals and DNA breaks while preserving its antitumour mechanism mediated through a calcium signalling pathway and arachidonic acid metabolism. Lipidomics profiling further revealed that ND-Nic-treated cells retained a metabolite profile characteristic of niclosamide-treated cells. Notably, quantitative scoring of drug sensitivity suggests that elimination of its nitro group enhanced the target selectivity of niclosamide against p53 deficiency. Importantly, the results also raise concern that niclosamide may impose a pleiotropic genotoxic effect, which limits its clinical efficacy and warrants further investigation into alternative drug analogues that may ameliorate any potential unwanted side effects.

Multi-omics profiling of CHO parental hosts reveals cell line-specific variations in bioprocessing traits.

Chinese hamster ovary (CHO) cells are the most prevalent mammalian cell factories for producing recombinant therapeutic proteins due to their ability to synthesize human-like post-translational modifications and ease of maintenance in suspension cultures. Currently, a wide variety of CHO host cell lines has been developed; substantial differences exist in their phenotypes even when transfected with the same target vector. However, relatively less is known about the influence of their inherited genetic heterogeneity on phenotypic traits and production potential from the bioprocessing point of view. Herein, we present a global transcriptome and proteome profiling of three commonly used parental cell lines (CHO-K1, CHO-DXB11, and CHO-DG44) in suspension cultures and further report their growth-related characteristics, and N- and O-glycosylation patterns of host cell proteins (HCPs). The comparative multi-omics and subsequent genome-scale metabolic network model-based enrichment analyses indicated that some physiological variations of CHO cells grown in the same media are possibly originated from the genetic deficits, particularly in the cell-cycle progression. Moreover, the dihydrofolate reductase deficient DG44 and DXB11 possess relatively less active metabolism when compared to K1 cells. The protein processing abilities and the N- and O-glycosylation profiles also differ significantly across the host cell lines, suggesting the need to select host cells in a rational manner for the cell line development on the basis of recombinant protein being produced.

Auroramycin: A Potent Antibiotic from Streptomyces roseosporus by CRISPR-Cas9 Activation.

Silent biosynthetic gene clusters represent a potentially rich source of new bioactive compounds. We report the discovery, characterization, and biosynthesis of a novel doubly glycosylated 24-membered polyene macrolactam from a silent biosynthetic gene cluster in Streptomyces roseosporus by using the CRISPR-Cas9 gene cluster activation strategy. Structural characterization of this polyketide, named auroramycin, revealed a rare isobutyrylmalonyl extender unit and a unique pair of amino sugars. Relative and absolute stereochemistry were determined by using a combination of spectroscopic analyses, chemical derivatization, and computational analysis. The activated gene cluster for auroramycin production was also verified by transcriptional analyses and gene deletions. Finally, auroramycin exhibited potent anti-methicillin-resistant Staphylococcus aureus (anti-MRSA) activity towards clinical drug-resistant isolates.

Excessive interferon-α signaling in autoimmunity alters glycosphingolipid processing in B cells.

Excessive interferon-α (IFN-α) production by innate immune cells is a hallmark of autoimmune diseases. What other cell type secretes IFN-α and how IFN-α affects immune cell metabolism and homeostasis in autoimmunity are largely unclear. Here, we report that autoimmune B cells, arising from two different B cell-specific genetic lesions in mice, secrete IFN-α. In addition, IFN-α, found in abundance in autoimmunity, elicited profound changes in the B cell lipidome, increasing their expression of glycosphingolipids (GSLs) and leading to their CD1d-mediated depletion of iNKT cells in vitro and in vivo. IFN-α receptor blockade could reverse the loss of iNKT cells. Excessive stimulation of B cells with IFN-α altered the expression of enzymes that catalyze critical steps in GSL processing, increasing the expressions of glucosylceramide synthase (GCS) and globotrihexosylceramide synthase (Gb3S) but decreasing that of α-galactosidase A (α-galA). Inhibiting GCS or restoring α-galA expression prevented iNKT depletion by IFN-α-activated B cells. Taken together, our work indicated that excessive IFN-α perturbs GSL metabolism in B cells which in turn adversely affects iNKT homeostasis.

An LC-MS-based lipidomics pre-processing framework underpins rapid hypothesis generation towards CHO systems biotechnology.

INTRODUCTION: Given a raw LC-MS dataset, it is often required to rapidly generate initial hypotheses, in conjunction with other 'omics' datasets, without time-consuming lipid verifications. Furthermore, for meta-analysis of many datasets, it may be impractical to conduct exhaustive confirmatory analyses. In other cases, samples for validation may be difficult to obtain, replicate or maintain. Thus, it is critical that the computational identification of lipids is of appropriate accuracy, coverage, and unbiased by a researcher's experience and prior knowledge. OBJECTIVES: We aim to prescribe a systematic framework for lipid identifications, without usage of their characteristic retention-time by fully exploiting their underlying mass features. RESULTS: Initially, a hybrid technique, for deducing both common and distinctive daughter ions, is used to infer parent lipids from deconvoluted spectra. This is followed by parent confirmation using basic knowledge of their preferred product ions. Using the framework, we could achieve an accuracy of ~ 80% by correctly identified 101 species from 18 classes in Chinese hamster ovary (CHO) cells. The resulting inferences could explain the recombinant-producing capability of CHO-SH87 cells, compared to non-producing CHO-K1 cells. For comparison, a XCMS-based study of the same dataset, guided by a user's ad-hoc knowledge, identified less than 60 species of 12 classes from thousands of possibilities. CONCLUSION: We describe a systematic LC-MS-based framework that identifies lipids for rapid hypothesis generation.

A simple and highly sensitive LC-MS workflow for characterization and quantification of ADC cleavable payloads.

Antibody-drug conjugates (ADC) payloads are cleavable drugs that act as the warhead to exert an ADC's cytotoxic effects on cancer cells intracellularly. A simple and highly sensitive workflow is developed and validated for the simultaneous quantification of six ADC payloads, namely SN-38, MTX, DXd, MMAE, MMAF and Calicheamicin (CM). The workflow consists of a short and simple sample extraction using a methanol-ethanol mixture, followed by a fast liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis. The results showed that well-validated linear response ranges of 0.4-100 nM for SN38, MTX and DXd, 0.04-100 nM for MMAE and MMAF, 0.4-1000 nM for CM were achieved in mouse serum. Recoveries for all six payloads at three different concentrations (low, medium and high) were more than 85%. An ultra-low sample volume of only 5 µL of serum is required due to the high sensitivity of the method. This validated method was successfully applied to a pharmacokinetic study to quantify MMAE in mouse serum samples.

Antibody glycan quality predicted from CHO cell culture media markers and machine learning.

N-glycosylation can have a profound effect on the quality of mAb therapeutics. In biomanufacturing, one of the ways to influence N-glycosylation patterns is by altering the media used to grow mAb cell expression systems. Here, we explore the potential of machine learning (ML) to forecast the abundances of N-glycan types based on variables related to the growth media. The ML models exploit a dataset consisting of detailed glycomic characterisation of Anti-HER fed-batch bioreactor cell cultures measured daily under 12 different culture conditions, such as changes in levels of dissolved oxygen, pH, temperature, and the use of two different commercially available media. By performing spent media quantitation and subsequent calculation of pseudo cell consumption rates (termed media markers) as inputs to the ML model, we were able to demonstrate a small subset of media markers (18 selected out of 167 mass spectrometry peaks) in a Chinese Hamster Ovary (CHO) cell cultures are important to model N-glycan relative abundances (Regression - correlations between 0.80-0.92; Classification - AUC between 75.0-97.2). The performances suggest the ML models can infer N-glycan critical quality attributes from extracellular media as a proxy. Given its accuracy, we envisage its potential applications in biomaufactucuring, especially in areas of process development, downstream and upstream bioprocessing.

Understanding and controlling the molecular mechanisms of protein aggregation in mAb therapeutics.

In antibody development and manufacturing, protein aggregation is a common challenge that can lead to serious efficacy and safety issues. To mitigate this problem, it is important to investigate its molecular origins. This review discusses (1) our current molecular understanding and theoretical models of antibody aggregation, (2) how various stress conditions related to antibody upstream and downstream bioprocesses can trigger aggregation, and (3) current mitigation strategies employed towards inhibiting aggregation. We discuss the relevance of the aggregation phenomenon in the context of novel antibody modalities and highlight how in silico approaches can be exploited to mitigate it.

The effect of inhibition of receptor tyrosine kinase AXL on DNA damage response in ovarian cancer.

AXL is a receptor tyrosine kinase that is often overexpressed in cancers. It contributes to pathophysiology in cancer progression and therapeutic resistance, making it an emerging therapeutic target. The first-in-class AXL inhibitor bemcentinib (R428/BGB324) has been granted fast track designation by the U.S. Food and Drug Administration (FDA) in STK11-mutated advanced metastatic non-small cell lung cancer and was also reported to show selective sensitivity towards ovarian cancers (OC) with a Mesenchymal molecular subtype. In this study, we further explored AXL's role in mediating DNA damage responses by using OC as a disease model. AXL inhibition using R428 resulted in the increase of DNA damage with the concurrent upregulation of DNA damage response signalling molecules. Furthermore, AXL inhibition rendered cells more sensitive to the inhibition of ATR, a crucial mediator for replication stress. Combinatory use of AXL and ATR inhibitors showed additive effects in OC. Through SILAC co-immunoprecipitation mass spectrometry, we identified a novel binding partner of AXL, SAM68, whose loss in OC cells harboured phenotypes in DNA damage responses similar to AXL inhibition. In addition, AXL- and SAM68-deficiency or R428 treatment induced elevated levels of cholesterol and upregulated genes in the cholesterol biosynthesis pathway. There might be a protective role of cholesterol in shielding cancer cells against DNA damage induced by AXL inhibition or SMA68 deficiency.

Muscle Injuries Induce a Prostacyclin-PPARγ/PGC1a-FAO Spike That Boosts Regeneration.

It is well-known that muscle regeneration declines with aging, and aged muscles undergo degenerative atrophy or sarcopenia. While exercise and acute injury are both known to induce muscle regeneration, the molecular signals that help trigger muscle regeneration have remained unclear. Here, mass spectrometry imaging (MSI) is used to show that injured muscles induce a specific subset of prostanoids during regeneration, including PGG1, PGD2, and the prostacyclin PGI2. The spike in prostacyclin promotes skeletal muscle regeneration via myoblasts, and declines with aging. Mechanistically, the prostacyclin spike promotes a spike in PPARγ/PGC1a signaling, which induces a spike in fatty acid oxidation (FAO) to control myogenesis. LC-MS/MS and MSI further confirm that an early FAO spike is associated with normal regeneration, but muscle FAO became dysregulated during aging. Functional experiments demonstrate that the prostacyclin-PPARγ/PGC1a-FAO spike is necessary and sufficient to promote both young and aged muscle regeneration, and that prostacyclin can synergize with PPARγ/PGC1a-FAO signaling to restore aged muscles' regeneration and physical function. Given that the post-injury prostacyclin-PPARγ-FAO spike can be modulated pharmacologically and via post-exercise nutrition, this work has implications for how prostacyclin-PPARγ-FAO might be fine-tuned to promote regeneration and treat muscle diseases of aging.

LC-MS-based metabolic characterization of high monoclonal antibody-producing Chinese hamster ovary cells.

The selection of suitable mammalian cell lines with high specific productivities is a crucial aspect of large-scale recombinant protein production. This study utilizes a metabolomics approach to elucidate the key characteristics of Chinese hamster ovary (CHO) cells with high monoclonal antibody productivities (q(mAb)). Liquid chromatography-mass spectrometry (LC-MS)-based intracellular metabolite profiles of eight single cell clones with high and low q(mAb) were obtained at the mid-exponential phase during shake flask batch cultures. Orthogonal projection to latent structures discriminant analysis (OPLS-DA) subsequently revealed key differences between the high and low q(mAb) clones, as indicated by the variable importance for projection (VIP) scores. The mass peaks were further examined for their potential association with q(mAb) across all clones using Pearson's correlation analysis. Lastly, the identities of metabolites with high VIP and correlation scores were confirmed by comparison with standards through LC-MS-MS. A total of seven metabolites were identified-NADH, FAD, reduced and oxidized glutathione, and three activated sugar precursors. These metabolites are involved in key cellular pathways of citric acid cycle, oxidative phosphorylation, glutathione metabolism, and protein glycosylation. To our knowledge, this is the first study to identify metabolites that are associated closely with q(mAb). The results suggest that the high producers had elevated levels of specific metabolites to better regulate their redox status. This is likely to facilitate the generation of energy and activated sugar precursors to meet the demands of producing more glycosylated recombinant monoclonal antibodies.

Combined in silico modeling and metabolomics analysis to characterize fed-batch CHO cell culture.

The increasing demand for recombinant therapeutic proteins highlights the need to constantly improve the efficiency and yield of these biopharmaceutical products from mammalian cells, which is fully achievable only through proper understanding of cellular functioning. Towards this end, the current study exploited a combined metabolomics and in silico modeling approach to gain a deeper insight into the cellular mechanisms of Chinese hamster ovary (CHO) fed-batch cultures. Initially, extracellular and intracellular metabolite profiling analysis shortlisted key metabolites associated with cell growth limitation within the energy, glutathione, and glycerophospholipid pathways that have distinct changes at the exponential-stationary transition phase of the cultures. In addition, biomass compositional analysis newly revealed different amino acid content in the CHO cells from other mammalian cells, indicating the significance of accurate protein composition data in metabolite balancing across required nutrient assimilation, metabolic utilization, and cell growth. Subsequent in silico modeling of CHO cells characterized internal metabolic behaviors attaining physiological changes during growth and non-growth phases, thereby allowing us to explore relevant pathways to growth limitation and identify major growth-limiting factors including the oxidative stress and depletion of lipid metabolites. Such key information on growth-related mechanisms derived from the current approach can potentially guide the development of new strategies to enhance CHO culture performance.

Harnessing the potential of machine learning for advancing "Quality by Design" in biomanufacturing.

Ensuring consistent high yields and product quality are key challenges in biomanufacturing. Even minor deviations in critical process parameters (CPPs) such as media and feed compositions can significantly affect product critical quality attributes (CQAs). To identify CPPs and their interdependencies with product yield and CQAs, design of experiments, and multivariate statistical approaches are typically used in industry. Although these models can predict the effect of CPPs on product yield, there is room to improve CQA prediction performance by capturing the complex relationships in high-dimensional data. In this regard, machine learning (ML) approaches offer immense potential in handling non-linear datasets and thus are able to identify new CPPs that could effectively predict the CQAs. ML techniques can also be synergized with mechanistic models as a 'hybrid ML' or 'white box ML' to identify how CPPs affect the product yield and quality mechanistically, thus enabling rational design and control of the bioprocess. In this review, we describe the role of statistical modeling in Quality by Design (QbD) for biomanufacturing, and provide a generic outline on how relevant ML can be used to meaningfully analyze bioprocessing datasets. We then offer our perspectives on how relevant use of ML can accelerate the implementation of systematic QbD within the biopharma 4.0 paradigm.

Applications and analysis of hydrolysates in animal cell culture.

Animal cells are used in the manufacturing of complex biotherapeutic products since the 1980s. From its initial uses in biological research to its current importance in the biopharmaceutical industry, many types of culture media were developed: from serum-based media to serum-free to protein-free chemically defined media. The cultivation of animal cells economically has become the ultimate goal in the field of biomanufacturing. Serum serves as a source of amino acids, lipids, proteins and most importantly growth factors and hormones, which are essential for many cell types. However, the use of serum is unfavorable due to its high price tag, increased lot-to-lot variations and potential risk of microbial contamination. Efforts are progressively being made to replace serum with recombinant proteins such as growth factors, cytokines and hormones, as well as supplementation with lipids, vitamins, trace elements and hydrolysates. While hydrolysates are more complex, they provide a diverse source of nutrients to animal cells, with potential beneficial effects beyond the nutritional value. In this review, we discuss the use of hydrolysates in animal cell culture and briefly cover the composition of hydrolysates, mode of action and potential contaminants with some perspectives on its potential role in animal cell culture media formulations in the future.