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Journal of Industrial Microbiology & Biotechnology logoLink to Journal of Industrial Microbiology & Biotechnology
. 2026 Mar 14;53:kuag008. doi: 10.1093/jimb/kuag008

Citric acid treatment of Tetradesmus obliquus biomass reduces dry matter loss in handling, queuing, and long-term storage, while stimulating auto-fermentative production of succinic acid

Bradley D Wahlen 1,✉, Chelsea C St Germain 2, Lynn M Wendt 3, John McGowen 4, Yaqi You 5
PMCID: PMC13049484  PMID: 41830930

Abstract

Post-harvest algae biomass is prone to degradation, resulting in mass loss and compositional changes, and preservation is vital to economic viability of algal products. Effective storage solutions are needed to mitigate for seasonal productivity variations (long-term storage) and to keep post-harvest biomass stable until processing. Ensiling has emerged as a long-term storage solution capable of preserving biomass up to 6 months with little loss without the energy demands of drying. Organic acids produced during ensiling lower biomass pH and prevent growth of degradative bacteria such as Clostridia. However, losses are front-loaded with a majority occurring within the first week before organic acids can accumulate. Currently, there is no information on the stability of algae biomass within the first 24 hr post-harvest or methods available to ensure stability during this period. Freshly harvested Tetradesmus obliquus UTEX 393 biomass was stored in three conditions: ambient atmosphere, anaerobic atmosphere without treatment, and anaerobic atmosphere with citric acid amendment. Citric acid treatment limited mass loss to 1% after 28 days, while untreated biomass experienced 4% mass loss after just 4 hr and 18% mass loss after 4 weeks. The carbohydrate fraction was most affected, with minimal changes to the elemental composition of biomass across treatments. Bacilli bacteria, including lactic acid bacteria, increased in abundance under all storage conditions. Untreated biomass showed a rise in Clostridia, but none were found in citric acid-treated biomass. After 28 days, organic acid composition differed significantly among treatments, with succinic acid being accumulated to 30% of dry cellular weight in citric acid treated UTEX 393 biomass. Citric acid treatment effectively mitigates biomass loss and, surprisingly, promotes substantial production of succinic acid. The unexpected autofermentation of UTEX 393 biomass to a versatile intermediate chemical such as succinic acid at high titers with minimal energy input could contribute to the economic viability of algae cultivation for fuels and chemicals.

One-Sentence Summary  Tetradesmus obliquus biomass is susceptible to degradation immediately after harvest; citric acid treatment preserves biomass while stimulating succinic acid accumulation.

Keywords: storage, post-harvest physiology, queuing, autofermentation, coproducts

Graphical Abstract

Graphical Abstract.

For image description, please refer to the figure legend and surrounding text.

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Introduction

Microalgae, due to its rapid growth rate and ability to be cultivated on marginal lands with non-potable water, has tremendous potential to meet the energy demands of society without competing with food production. The tolerance of microalgae to a wide range of water quality and its ability to rapidly assimilate nutrients (e.g., nitrogen and phosphorus) have led microalgae cultivation to be increasingly adopted as a cost-effective approach to wastewater treatment (Zhao et al., 2018). Its favorable and diverse biochemical composition makes it an ideal feedstock for producing a wide range of products (de Souza et al., 2019). High concentration of lipids supports the production of fuels for difficult-to-electrify segments of the economy, such as aviation, agriculture, and shipping (Greene et al., 2025). Additionally, the high content of polyunsaturated fatty acids within these lipids makes microalgae a useful source of essential fatty acids for nutritional supplementation or the production of polyurethanes (Barta et al., 2021; Dong et al., 2021). A number of approaches have been developed to produce fuels and chemicals or animal feed from the carbohydrate and protein fraction of algae biomass (Dong et al., 2016; Liu et al., 2019; Quiroz-Arita et al., 2022) and hydrothermal liquefaction can effectively convert whole algal biomass to a biocrude that can be refined into a number of products (Valdez et al., 2012). In order for the biotechnological potential of algae to be realized, biomass quality must be maintained during harvesting, storage, and handling until the final product can be made.

Once harvested, microalgae biomass is susceptible to degradation due to its high moisture content, accessible carbohydrates, supply of nitrogen (as protein) and the associated microbiome. Open raceway cultivation is seen as the most economical approach to algae biomass production (Richardson et al., 2012); however, this approach allows for environmental contamination of the culture with bacteria, fungi, and zooplankton grazers, which can reduce productivity and, in the extreme, lead to pond crashes (Carney et al., 2016; Park et al., 2019). Once harvested, the microbiome associated with algae biomass could contribute to its rapid degradation. Thus understanding the microbial community dynamics of algae biomass is a primary concern for developing logistics and handling approaches for algae biorefineries (Wahlen et al., 2023). Stability studies conducted on harvested algae biomass have shown that losses up to 44% can occur over 30 days (Wendt et al., 2017), with mass losses occurring primarily in the carbohydrate fraction of the biomass (Wendt et al., 2019). In addition to mass loss that can occur as a result of bacterial metabolism, harvested algae biomass can experience algae-induced mass loss as they metabolize internal carbon stores to maintain cellular processes once they are unable to conduct photosynthesis (Ogbonna & Tanaka, 1996). Nighttime losses in algae culture have been measured at 2%–10% of the biomass prior to darkening in a single night (Edmundson & Huesemann, 2015; Grobbelaar & Soeder, 1985).

Storage of algae biomass is needed to maintain the quality and quantity of algae biomass to mitigate seasonal variation in productivity (long-term) and to manage daily fluctuations in production and processing capacity (queuing). Long-term storage can be needed for up to 6 months, while queuing operates on a much shorter timescale over hours to days. Long-term preservation of microalgae biomass has been successfully achieved by ensiling, storing algae biomass from high productivity seasons (spring-summer) for use in low productivity seasons (fall-winter) (Wendt et al., 2020). Ensiling, an approach for long-term stabilization, is commonly used to preserve forage crops for livestock feed through the winter (Wilkinson et al., 2003). Successful ensiling relies on lactic acid fermentation of available carbohydrates in an anaerobic environment to produce lactic acid and a reduced pH, which together limit bacterial degradation of the ensiled biomass (Borreani et al., 2018). Ensiling has successfully preserved algae biomass alone or blended with lignocellulosic biomass for 180 days with <10% loss (Oginni et al., 2022; Wahlen et al., 2019). Ensiling as an approach to preservation was found to decrease the minimum fuel selling price (MFSP) of algae biofuels by $0.32 per gallon of gasoline equivalent compared to drying (Wendt et al., 2019), with an additional $0.14 reduction in MFSP by recovering organic acids (e.g., succinic acid) produced in storage for sale as a co-product (Wendt et al., 2019).

Biomass losses observed in algae storage studies did not occur at the same rate throughout the storage period (Oginni et al., 2022; Wahlen et al., 2019). Loss rates were higher in the first 30 days and decreased after that. It takes time to establish low pH conditions through lactic acid fermentation and the timeframe in which this occurs, days to weeks, is compatible with long-term seasonal storage (up to 180 days) but may be less relevant to queuing scenarios (hours to days). While long-term preservation is anticipated to affect 16% of the total annual biomass yield (Wendt et al., 2019), all post-harvest algae biomass can experience delays in processing of uncertain lengths of time. At present, no studies have examined the quality impacts of delayed processing on algae biomass. This study will evaluate changes in biomass quantity and quality over the first 24 hr post-harvest (queuing scenario) compared against changes occurring over 30 days in a long-term preservation scenario. In addition to compositional changes, the study will follow changes occurring to the microbial community and will measure organic acid fermentation products to understand better lactic acid fermentation dynamics and microbial turnover. The outcome of untreated biomass will be compared to biomass treated with citric acid, an organic acid often used in food preservation and demonstrated to improve silage quality of terrestrial crops (Chen et al., 2021; Lv et al., 2020).

Materials and methods

Algae biomass

Tetradesmus obliquus UTEX393 algae strain used in this study was grown in a 2000 L raceway at Arizona Center for Algae Technology and Innovation (AzCATI, Mesa, AZ, USA) in October of 2019, as described previously (McGowen et al., 2023). Pond water temperature averaged a low of 11.5 °C and a high temperature of 22 °C from the previous biomass harvest to the time this study was undertaken. The algal biomass was dewatered at 1800 × g through Lavin 20–1160 V Centrifuges (AML Industries, Inc., Warren, OH, USA) with a flow rate of approximately 2 L/min and dewatered to 20% solids.

Queuing and storage stability studies

This study was initiated at AzCATI where the biomass could be directly received from the centrifuge to minimize time between harvest and start of the storage experiment. 2.1 kg of wet algae biomass was collected, of which 1.3 kg was used in untreated storage studies (anaerobic and ambient) and 750 g was utilized in citric acid-treated studies. Algae for untreated conditions (ambient and anaerobic) was added to 250 ml serum vials without modification (∼30 g, wet basis). Vials for the anaerobic condition were sealed with a butyl rubber septum and the headspace was exchanged for nitrogen gas. Vials for the ambient condition were closed with a septum but not sealed to permit periodic exposure to ambient atmosphere. For citric acid-treated biomass, 750 g of UTEX393 biomass was mixed with citric acid (1% w/w, wet basis) in a plastic bag prior to distributing to 250 ml serum vials (∼35 g, wet basis). Citric acid-treated vials were sealed and stored anaerobically as described above. Vials were allowed to incubate at room temperature (∼22 °C) in the dark for up to 28 days. Queuing stability was assessed by sampling vials after 4, 8, and 24 hr post-harvest. Each unsealed vial was weighed and then flash frozen at −80 °C to be returned to Idaho National Laboratory in Idaho Falls, ID. Once in Idaho, samples were allowed to thaw on ice. Subsamples of each vial were taken for moisture analysis, organic acid content and composition measurement and 16S rRNA gene sequencing to characterize microbial communities. The moisture content of the initial and stored biomass was determined gravimetrically after drying at 105 ⁰C until a constant weight was reached. Dry matter loss (DML) was determined as described previously (Wendt et al., 2017).

Carbohydrate analysis

Total carbohydrates for initial and stored biomass were determined as outlined by the NREL Laboratory Analytical Procedure (Van Wychen & Laurens, 2015, NREL/TP-5100-60957). Briefly, the samples were incubated with sulfuric acid (72% w/w) for 1 hr at 30 ⁰C with recurrent mixing. Acidified samples were then diluted to 4% acid (w/w) and autoclaved for 1 hr at 121 ⁰C. The samples were cooled and then neutralized with calcium carbonate and filtered with a 0.22 µm nylon filter. Samples were measured in duplicate by high performance liquid chromatography (HPLC). The HPLC refractive index detector (1200 series, Agilent, Santa Clara, CA, USA) was calibrated with a five-component carbohydrate standard at 5 different concentrations in triplicate (P/N 13528, Absolute Standards Inc., Hamden, CT, USA) and validated with a five-component check standard (P/N S-16632-R5, Accustandard, Inc., New Haven, CT, USA). Analyte peaks in each sample were quantified using standard retention times and calibration curves of the standards compounds.

CHNS analysis

Prior to analysis, algae biomass was lyophilized and then ground fine with a mortar and pestle. Elemental analysis of algae samples were determined using a LECO TruSpec CHN and S add-on module (St. Joseph, MI, USA) following ASTM D5373-10 (ASTM-D4239-10, 2010) and ASTM D4329 (ASTM-D5373-21, 2021) to determine carbon (C), hydrogen (H), nitrogen (N), and sulfur (S) content. In order to have enough material for this analysis, the ground material from biological replicates (n = 3) were combined into a single sample.

Organic acid analysis

Biomass (initial and stored material) was resuspended as a 1:10 dilution (w/v) in nano-pure water in a 50 ml falcon tube. The samples were vortexed and stored at 4 °C for 24 hr to allow extraction of organic acids. The algae cells were then removed by an initial centrifugation step at 8000 x g for 5 min. The supernatant was then filtered through a 0.22 µm nylon filter to remove particulates and acidified with H2SO4 to a final concentration of 0.4 N. Each sample was analyzed in duplicates by HPLC equipped with a refractive index detector (1200 series, Agilent, Santa Clara, CA, USA). Organic acids were separated by an Aminex HPX 87H ion exclusion column (P/N 125-0140, Bio-Rad, Hercules, CA, USA) and standardized using a ten-component organic acid standard (P/N 95917, Absolute Standards Inc. Hamden, CT, USA) at five different levels. Quantification of each identified analyte was performed using a calibration curve for the matching compound.

DNA extraction, purification, and evaluation

DNA was extracted from algae samples using the DNeasy PowerSoil Pro Kit (QIAGEN, Germantown, MD, United States) according to the manufacturer’s protocol as before (Wahlen et al., 2023; You et al., 2021). Extracted DNA was eluted in 50 µl and further purified using ethanol precipitation (Green & Sambrook, 2016). A NanoDrop 1000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, United States) was used to evaluate the quantity and quality of DNA. A random selection of DNA extracts were also evaluated by gel electrophoresis. The DNA samples were stored at −20 °C before further processing.

Library preparation and Illumina sequencing

Amplicon libraries were prepared in a similar manner to the Earth Microbiome project and as has been done previously (Caporaso et al., 2012; Wahlen et al., 2023; You et al., 2021). The V4 region of the 16S rRNA gene of archaea and bacteria was amplified by polymerase chain reaction (PCR) using the Invitrogen Platinum Hot Start PCR 2X Master Mix (Thermo Fisher Scientific, Waltham, MA, United States). The PCR reaction consisted of 20 ng of template DNA, 0.2 μM of forward-barcoded 515F primer (5′-3′: GTGYCAGCMGCCGCGGTAA), 0.2 µM 806R primer (5′-3′: GGACTACNVGGGTWTCTAAT), and nuclease free water in a total volume of 25 μl (Apprill et al., 2015; Parada et al., 2016; Walters et al., 2016). To avoid matrix effects, no more than 5 µl of DNA template solutions were used. Thermal cycler (Applied Biosystems, Waltham, MA, United States) conditions were: 94 °C for 3 min, followed by 35 cycles of 94 °C for 45 se, 50 °C for 60 s, and 72 °C for 90 s, and a final extension at 72 °C 10 min. Each PCR run also included a negative control using nuclease free water as template.

Triplicate PCR reactions from the same DNA sample were pooled into a single library and cleaned up using MagBio HighPrep PCR Clean-up System (Illumina, San Diego, CA, United States) by following the Illumina PCR Clean-up 2 protocol (Wei, https://dx.doi.org/10.17504/protocols.io.nb5daq6). The quantity and quality of the library were assessed by qPCR with the NEBNext Library Quant Kit for Illumina (New England BioLabs, Ipswich, MA, United States) on a CFX96 Touch Real-Time PCR System (Bio-Rad, Hercules, CA, United States), and on a 5200 Fragment Analyzer (Agilent Technologies, Santa Clara, CA, United States) utilizing the High Sensitivity NGS Fragment Kit (Agilent Technologies, Santa Clara, CA, United States).

Libraries were evaluated by gel electrophoresis and quantified using QuantiFluor dsDNA HS System (Promega, Madison, WI, United States) on a Qubit 4.0 Fluorometer (Thermo Fisher Scientific, Waltham, MA, United States). The libraries were pooled in equimolar concentrations. Sequencing was conducted on a MiSeq platform (Illumina, San Diego, CA, United States) following the manufacturer’s guide, using the MiSeq Reagent Kit v2 (2 × 250 bp, Illumina, San Diego, CA, United States). PhiX control v3 was used as a quality control for sequencing runs, with a spike of 3%–5% (increased to 10% if low sample diversity was observed).

Bioinformatic analysis

Paired-end reads were quality controlled using FastQC (https://www.bioinformatics.babraham.ac.uk/projects/fastqc) and raw sequences were demultiplexed in Qiime2 and then processed using the Mothur MiSeq SOP (Kozich et al., 2013). Briefly, paired-end reads were merged into contigs, screened for quality and the SILVA 16S rRNA database (v 138) was used for alignment (Wahlen et al., 2023). The VSEARCH algorithm was used to identify and remove chimeras. Remaining sequences were classified using a Bayesian classifier and SILVA 16S rRNA reference files (v 138). Sequences not classified as prokaryotes were removed. OptiClust was used to cluster sequences into operational taxonomic units with a distance cutoff of 3%. Rarefaction was set to 7,666 to provide for even sampling. A non-dimensional multiple scaling (Supplementary Figure 1) ordination using Yue and Clayton measure of dissimilarity, measures communities in post-harvest Tetraselmis obliquus UTEX 393 biomass according to treatment and time post-harvest.

Statistical analysis

The data were analyzed and graphed in RStudio (v.4.1.2) using the following packages: tidyverse, RColorBrewer, ggtext, svglite, ggplot2, dplyr, and ggpubr. Analysis of variance (ANOVA) analyses followed by post-hoc Tukey’s Honestly Significant Difference test (HSD) analyses were performed in RStudio to determine significant changes between levels in moisture content, pH, or OA profiles. For microbiome analysis, microbial classes or genus with greater than 4% abundance are represented by their group name. All others with abundance <4% are grouped together as ‘Other’.

Results

Queuing stability

The queuing operation in the context of a biorefinery is short-term storage at the refinery gate to ensure a constant supply of material. A microalgae biofuel conversion design case considers a surge capacity (i.e., queuing capacity) of 24 hr to accommodate variations in algae productivity and utilization (Davis et al., 2014, NREL/TP-5100-62 368). The fate of microalgae quality during this process is not known and this knowledge gap can be a barrier to commercial production of fuels and chemicals from microalgae.

The stability of just-harvested Tetradesmus obliquus UTEX 393 biomass (20% solids) during the queuing operation was assessed at the Arizona Center for Algae Technology Innovation (AzCATI) under three different conditions over a 24-hr period: (1) under an ambient atmosphere, (2) under an anaerobic atmosphere, and (3) under an anaerobic atmosphere after first being treated with citric acid (1% w/w, wet basis). Other research in our lab suggested citric acid amendment of algae biomass could reduce material loss in storage (data not shown). Citric acid has been shown to improve silage quality in terrestrial crops (Chen et al., 2021; Lv et al., 2020). We therefore evaluated its effect on stability in post-harvest microalgae biomass. The impact of the three incubation conditions on quantity and quality of biomass was evaluated in triplicate after 4, 8, and 24 hr. As a comparison to queuing stability, biomass stability after 28 days, representative of long-term storage, was also evaluated.

Post-harvest algae biomass experienced an immediate negative impact to material quantity. Just 4 hr after harvest, the untreated biomass incubated under ambient conditions lost 4.1% (dry basis) of material, while biomass incubated under anaerobic conditions lost 3.5% (dry basis) (Table 1). In contrast, when algae biomass was amended with citric acid prior to incubation no loss was experienced over the same period of time (−0.6% ± 1.2%, dry basis), indicating that citric acid was effective at preventing initial degradation of harvested algae biomass. After 24 hr algae biomass treated with citric acid had only lost 1.2% ± 1.1% of dry basis compared to 4.2% for untreated biomass under ambient and anaerobic conditions. Material losses observed in both anaerobic and ambient conditions were remarkably similar and did not increase appreciably from 4 hr (3.5% and 4.1%, respectively) to 24 hr (4.2%), indicating that beyond the initial loss the material was generally stable. The similarity in stability between ambient and anaerobic treatments likely results from a combination of rapid oxygen consumption by cellular respiration and limited oxygen penetration into the 20% solids algae biomass, which had a paste like consistency. In solid-state fermentation systems with comparable moisture contents and biomass densities, oxygen has been shown to penetrate only 60–100 μm into wet biomass layers (Oostra et al., 2001). Diffusion limitations through biofilms permit anaerobic bacteria to thrive in aerobic environments when the biofilms have a thickness >25 μm (Stewart, 2003). Given that the experimental setup used in this study had algae paste at a much greater thickness (several centimeters), functionally anaerobic conditions would be expected to develop in both treatments irrespective of headspace atmosphere.

Table 1.

Biomass stability in queuing and long-term storage as determined by dry matter loss, pH, and total organic acid content.

Dry matter loss (%, dry basis) pH Total organic acid (%, dry basis)
Untreated Untreated Untreated
Time Ambient Anaerobic Citric acid Ambient Anaerobic Citric acid Ambient Anaerobic Citric acid
0 – – – 6.24 6.24 5.34 0.3 0.3 0.3
4 hr 4.1 ± 0.6 3.5 ± 0.3 -0.6 ± 1.2 6.36 ± 0.01 6.33 ± 0.03 4.74 ± 0.01 3.1 ± 0.7 1.0 ± 0.6 2.9 ± 1.1
8 hr 2.8 ± 0.7 3.6 ± 0.4 0.4 ± 0.6 6.40 ± 0.02 6.37 ± 0.01 4.83 ± 0.04 4.0 ± 0.6 3.0 ± 0.9 3.1 ± 0.1
24 hr 4.2 ± 0.1 4.2 ± 0.6 1.2 ± 1.1 6.41 ± 0.02 6.30 ± 0.03 6.75 ± 0.04 2.4 ± 1.6 3.0 ± 1.0 2.8 ± 0.1
28 days 18.1 ± 8.0 *17.8 ± 0.2 0.4 ± 1.5 6.36 ± 0.01 *6.53 ± 0.03 4.67 ± 0.03 16.3 ± 3.5 *10.4 ± 1.0 38.5 ± 5.5
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*

Average of two replicate storage experiments. All other data are the results of three biological replicates.

The biomass pH also changed within the 24-hr queuing period. The untreated biomass started with a pH of 6.24. This increased slightly for both the ambient (6.41 ± 0.02) and anaerobic (6.30 ± 0.03) conditions over 24 hr (Table 1). The citric acid sample experienced greater change and variability in pH. After citric acid addition the biomass pH was initially 5.34 and decreased at first to 4.74 after 4 hr but then rose to 6.75 ± 0.04 after 24 hr. This temporary rise likely reflects the consumption of citric acid by the developing microbial community at a higher rate than the accumulation of lactic and succinic acids. By 28 days, lactic and succinic acids had reached greater quantities, achieving the final pH of 4.67. Total organic acids, excluding citric acid, for any condition in the first 24 hr were not statistically different (Table 1).

Long-term stability

Prior to this study there had not been a comparison between initial post-harvest losses and those that might occur during long-term storage. In addition to samples taken within the first 24 hr post-harvest, samples were also allowed to remain in each of the three storage conditions for up to 28 days to determine long-term impacts to biomass quantity and quality. Dry matter loss in untreated algae biomass stored under either an ambient atmosphere or anaerobic conditions was similar at 18.1% and 17.8%, respectively (Table 1). Algae biomass amended with citric acid, on the other hand, experienced 0.4% ± 1.5% dry matter loss over the same period, with no additional loss beyond what occurred in the first 24 hr. Material that is well-ensiled, often reaches pH values of 3.8–4.5 (Pahlow et al., 2003). A goal of this study was to achieve a pH below 4.5 in long-term stored algae biomass. This was nearly achieved for citric acid treated samples where the final pH reached 4.7. Both ambient atmosphere and anaerobic conditions ended with pH values that were much higher (6.4 and 6.5, respectively) but not too different from the initial value of 6.2. Total organic acid concentration after 28 days was much higher than the amount observed after 24 hr for all samples (Table 1). Samples in ambient conditions saw organic acid accumulate to 16% of total biomass (dry basis), while those in anaerobic conditions were less at 10% (dry basis). Citric acid treated samples were significantly different with organic acids accounting for nearly 40% of total biomass (dry basis). This will be discussed in greater detail in the organic acid content section.

Elemental composition

The impact of queuing and storage on biomass elemental composition was determined for 24-hr and 28-day samples from anaerobic and citric acid treatment condition and compared to that of the initial biomass (Table 2). The ambient condition was not evaluated as both anaerobic and ambient were similar in terms of dry matter loss and final pH. Algae biomass had an initial carbon content of 50.7%, higher than other bioenergy feedstocks, such as corn stover (48.7%) (“U.S. Department of Energy, Idaho National Laboratory, G43, ‘Bioenergy Feedstock Library,’ bioenergylibrary.inl.gov (accessed, July 2024),”). Additionally, nitrogen content in microalgae biomass far exceeded that of other bioenergy feedstocks, such as corn stover (9.5% vs. 0.7%, respectively). High protein content in algae is a consequence of cultivation conditions to achieve high-rate algal productivity. Carbon content increased slightly for the anaerobic treatment at both 24 hr and 28 days (Table 2). Carbon content was slightly lower for citric acid-treated biomass after 28 days storage and oxygen content was higher. This could be attributed to high concentrations of succinic acid present, which will be discussed in greater detail in the following section. As a dicarboxylic acid, succinic acid contains a higher proportion of oxygen content compared to the other observed organic acids.

Table 2.

Effect of queuing and long-term storage on elemental composition of UTEX 393 biomass.

Treatment Timepoint %C %H* %N %O %S*
Initial Biomass 0 hr 50.7 ± 0.5a 6.8 ± 0.8 9.5 ± 0.1a 32.4 ± 1.4a,b 0.6 ± 0.1
Untreated 24 hr 51.4 ± 0.1b 6.9 ± 0.1 10.0 ± 0.0b 31.2 ± 0.2a 0.7 ± 0.0
(Anaerobic) †28 day 51.5 ± 0.1b 7.1 ± 0.1 9.6 ± 0.0a 31.1 ± 0.2a 0.7 ± 0.0
Citric Acid 24 hr 50.7 ± 0.1a 7.1 ± 0.3 9.4 ± 0.1a 32.1 ± 0.3a 0.7 ± 0.1
Treated 28 day 50.0 ± 0.3c 6.7 ± 0.3 9.2 ± 0.2c 33.5 ± 0.4b 0.6 ± 0.1
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Each value is the mean of biological replicates which were measured in triplicate except for those marked with †, which were the mean of a single sample measured in triplicate. Variability is denoted by the standard deviation. For each group, the means with the same letter were not significantly different for p < 0.05 as determined by ANOVA analysis with pairwise comparison (Holm–Sidak method). Means with two or more letters were not significantly different from means marked with any of the letters. Columns marked with an asterisk (*) had no values that were significantly different.

Organic acid content

During queuing, little difference developed in the quantity and composition of organic acids within each treatment or among treatments (Figure 1A). The dominant organic acid was succinic acid, which was present between 1.5% and 3%, followed by propionic acid (≤1%). Both succinic acid and propionic acid were present in the initial biomass but at a much lower concentration. Lactic acid developed in samples treated with citric acid but not in any of the other treatments. Lactic acid concentration increased from 4 to 8 hrs but did not increase after 24 hr, with concentrations not exceeding 1%. Butyric acid was not found in any of the samples in the first 8 hr post-harvest and was detected in minor concentration at 24 hr. Acetic acid and isovaleric acid were lowest in citric acid-treated biomass. No citric acid treated samples exhibited butyric acid production in the first 24 hr post-harvest.

Figure 1.

For image description, please refer to the figure legend and surrounding text.

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The effect of queuing (4–24 hr) and storage (28 days) on the organic acid content of Tetradesmus obliquus UTEX 393 biomass incubated in an ambient atmosphere (A), anaerobic atmosphere (An), and an anaerobic atmosphere after treatment with citric acid (CA). (A) Organic acid profile during first 24 hr post-harvest (queuing). Treatments are compared to the initial biomass (T0). (B) Organic acid profile at 28 days (storage) for all treatments. Each bars represents the average of organic acid content from triplicate stability experiments; error bars represent the standard deviation. The 28-day anaerobic sample is an exception; values are the average of duplicate studies due to the loss of a replicate.

After 28 days, there was a significant change in the organic acid profile (Figure 1B). Most notably, succinic acid content in citric acid treated biomass increased markedly to account for 30% of the total biomass (dry basis), which is a 15-fold increase compared to the 24-hr timepoint. In contrast, the succinic acid content of each of the other conditions was reduced by more than half. Succinic acid production in storage (28 days) was limited to biomass treated with citric acid. The concentration of other organic acids also changed considerably in storage compared to queuing (Figure 1B). Acetic acid, which was present in very low concentrations 24 hr after harvest, accumulated to between 2.5% and 5% (w/w, dry basis) and was present in all three conditions. Propionic acid increased for each treatment during long-term storage, reaching concentrations between 2% and 3% (w/w, dry basis). Butyric acid, found in trace amounts after 24 hr was present in concentrations between 2.5% and 3% (w/w, dry basis) for both non-citric acid conditions after 28 days storage. Butyric acid was not present in citric acid treated biomass after 28 days. Isovaleric and lactic acids were present in each condition but was highest in citric acid treated biomass.

Microbial community analysis

The dynamic change in the microbial community composition in post-harvest Tetradesmus obliquus UTEX 393 biomass was followed using 16S rRNA gene sequencing (Figure 2). Four samples from the initial biomass and one sample from each condition at 4 and 8 hr were sequenced. Triplicate samples from each storage condition at 24 hr and 28 days were sequenced, except for the anaerobic condition at 28 days where only two replicates were sequenced, owing to the loss of one replicate during the storage experiment. Data from 4, 8, and 24 hr can be found in supplemental information. Changes to the microbial community within the first 24 hr were minimal, differing in relative abundance but not the identity of prominent classes or genera of bacteria.

Figure 2.

For image description, please refer to the figure legend and surrounding text.

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Effect of treatment and storage time on bacterial community composition at the class level. Bars represent the mean relative abundance of bacterial classes averaged across biological replicates (n = 3, except for T0, n = 4 and An 28d, n = 2) for each treatment-time combination. Classes with maximum relative abundance <5% across all samples were grouped as “Other.” Storage conditions included ambient atmosphere (“A”), anaerobic atmosphere (“An”), and citric acid treatment (“CA”). Data for 4 and 8 hr can be found in Supplementary Figure 2.

The community composition of the initial post-harvest algae biomass consisted of 11 classes of bacteria that exceeded the threshold of 5% relative abundance (Figure 2). Alphaprotobacteria and Cyanobacteria composed greater than 50% of total operational taxonomic units on average in the initial biomass, despite variance across replicates. These classes, particularly Cyanobacteria, were reduced substantially due to storage for all conditions. Bacteria from the Bacilli and Clostridia classes were absent in 2 of 4 initial samples and present at 1% relative abundance or lower in the other two samples. After 28 days of storage, Bacilli was present in untreated samples (ambient and anaerobic atmospheres) with a 9%–44% relative abundance and Clostridia composed between 8% and 47% of the microbial community. When treated with citric acid prior to storage, Bacilli composed between 27% and 77% of the community, while Clostridia was limited to less than 1% relative abundance.

Analysis of the impact of storage on the top genera in the community revealed a similar story (Figure 3). Lactic acid bacteria were present in all samples after 28 days of storage. However, the genus Lactobacillus was enriched in samples treated with citric acid prior to storage, reaching a relative abundance of up to 60%. Another genus of lactic acid bacteria, Lactococcus, was enriched under anaerobic conditions, but more without citric acid treatment. Interestingly, genera from the class Clostridia, such as Clostridium sensu stricto, were present at relative abundances as high as 25% in untreated samples but absent in all but one sample (0.2%) treated with citric acid.

Figure 3.

For image description, please refer to the figure legend and surrounding text.

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Changes in bacterial community composition at the genus level in response to treatment and storage time. Each cell represents mean relative abundance averaged from biological replicates (n = 3, except for T0, n = 4 and An 28d, n = 2). Genera not exceeding 5% relative abundance in any sample were grouped as “Other.” A, ambient atmosphere; An, anaerobic atmosphere; CA, citric acid. Data for 4 and 8 hr can be found in Supplementary Fig. 3.

Discussion

This study addresses a gap in our understanding of how processing delays impact post-harvest algae biomass and evaluates an approach to improve quality. Among bioenergy feedstocks, algae biomass is particularly susceptible to loss and quality deterioration due to its moisture and nutrient content. Unlike lignocellulosic feedstocks, such as corn stover or forest residues, algae are harvested during peak metabolic fitness, which can contribute to losses in storage as microalgae switch from a photosynthetic metabolism to one reliant on stored energy to maintain cellular processes (Atteia et al., 2013; Catalanotti et al., 2013; Edmundson & Huesemann, 2015). It is estimated that a nightly switch from photosynthesis to respiration or fermentation during cultivation could lead to overnight losses of 6.8% on average, impacting daily biomass productivity (Edmundson & Huesemann, 2015). In this study, losses of 4% were observed within the first 4 hr, comparable to the nightly losses observed by Edmundson and Huesemann (Edmundson & Huesemann, 2015). Interestingly, losses beyond 4% were not observed within the first 24 hr.

This study evaluated three storage conditions for algae biomass (20% solids): (1) ambient atmosphere, (2) anaerobic atmosphere, and (3) citric acid treated biomass in an anaerobic atmosphere. There was little difference between the storage performance of biomass in the ambient condition and that of the anaerobic condition. A higher rate of degradation was expected in the ambient atmosphere condition, where the higher oxygen content could support higher metabolic activity through respiration. The similarity in stability between the two conditions could be due to mass transfer limitations within the algae biomass, which at 20% solids has the consistency of a paste. With exception of the top layer, the biomass likely experienced the same anaerobic environment regardless of the concentration of oxygen in the jar headspace. Similarities observed in the organic acid composition, dry matter loss, final pH and elemental composition support this observation.

In addition to losses facilitated by algae metabolism, bacteria contribute to degradation by consuming extracellular carbohydrates, lipids and proteins. Ensiling is an approach that limits microbial metabolism. Successful ensiling of forage crops is characterized by a pH below 4.5, caused by lactic acid fermentation from lactic acid bacteria, including strains from the genus Lactobacillus. On the other hand, poorly ensiled material is often characterized by pH values above 4.5 and butyric acid accumulation caused by the growth of Clostridia strains (Pahlow et al., 2003). Although none of the conditions here achieved pH values below 4.5, the citric acid-treated biomass came close after 28 days in storage (pH = 4.7). Prior to this study, it wasn’t clear how quickly the microbial community would shift in response to harvest and post-harvest storage conditions. A number of studies followed microbial community dynamics in algae cultivation but studies looking at post-harvest biomass are not available (Ferro et al., 2020; Fulbright et al., 2018). The microbial community largely resembled the initial community over the first 24 hr in storage, indicating that microbial succession takes longer than a day under the study experimental conditions (Supplementary Figure 1). The most abundant genera were also similar between the initial post-harvest algae biomass and the stored biomass (all treatment conditions) within the first 24 hr (Supplementary Figure 2). In a study of microbial dynamics during corn ensiling, Lactobacillus species did not begin to increase in number until after 1 day, similar to what was observed here (Keshri et al., 2018). In a study on alfalfa silage, it was noted that the species prevalence of lactic acid bacteria changes with ensiling conditions. In the early phase of alfalfa ensiling (3 days), Pediococcus was the dominant lactic acid bacteria, while Lactobacillus became more abundant during the later stage of ensiling (day 30) when pH was lower. These studies along with the present study, suggest that significant changes to the microbial community in ensiling conditions occur on the order of days and weeks indicating that changes to stored algae biomass in the first day might be more impacted by algae metabolism than that of bacteria.

Long-term storage (28 days) saw significant changes to the microbial community for all treatment conditions. For untreated biomass (ambient and anaerobic atmospheres), bacteria from Bacilli and Clostridia classes increased in abundance. Citric acid treatment inhibited the growth of Clostridia and stimulated Bacilli more than either of the non-citric acid conditions. Microbiome engineering is a growing field that seeks to alter the microbiome in ways that improve human health, increase agricultural yield, improve environmental health or contribute to the production of bioenergy (Sheth et al., 2016). Applying this tool or approach has led to improvements in post-harvest stability of microalgae biomass for long-term storage but might be less impactful at addressing biomass stability in the queuing context (Wendt et al., 2019). Previously, we reported on how nitrogen management in algae cultivation can affect the microbiome that develops during storage in post-harvest algae biomass (Wahlen et al., 2023). In the current study, the addition of citric acid achieved a similar result, inhibiting undesirable microbes (Clostridia) and increasing abundance of beneficial bacteria (lactic acid bacteria).

Establishing rapid lactic acid fermentation is important to keeping Clostridia from increasing in abundance during ensiling (Pahlow et al., 2003). This can be achieved by increasing the initial concentration of lactic acid bacteria through inoculation, supplying water soluble carbohydrates for promoted lactic acid fermentation, reducing water activity by reducing water content or by treating biomass with an additive (Pahlow et al., 2003). In the case of the current study, the addition of citric acid prevented the growth of Clostridia and encouraged the growth of lactic acid bacteria. Within 4 hr of storage, biomass treated with citric acid began to accumulate lactic acid, demonstrating early activity of lactic acid bacteria. Lv et al. (2020) observed a similar result in Amomum villosum silage treated with citric acid, where Pediococcus and Lactobacillus increased with citric acid treatment, and their numbers remained low in the first week of ensiling but increased substantially after 14 and 30 days. Untreated UTEX 393 biomass in this study did not exhibit lactic acid fermentation and saw the beginnings of butyric acid production at 24 hr. The citric acid concentration used in this study (1% w/w wet basis, approximately 52 mM) is comparable to the 50 mM concentration demonstrated to inhibit Clostridium growth (Graham & Lund, 1986), supporting the observed inhibition of Clostridia in our citric acid-treated samples.

Citric acid treatment was evaluated in this study as an approach to improve storage performance in microalgae biomass. Challenges to ensiling algae biomass, such as high moisture content, variable biochemical composition (at times low water-soluble carbohydrates), and a robust microbial community that would resist modification through inoculation, have been noted in this manuscript and elsewhere (Cabrita et al., 2017). Citric acid was expected to reduce biomass pH, inhibit spoilage microbes and retain biomass quality in storage. Increased abundance of lactic acid bacteria due to citric acid amendment was not expected but contributed to the positive storage outcome desired. In addition to storage performance benefits, citric acid stimulated the production of high amounts of succinic acid approaching 30% dry cellular weight. Its source, algal or bacterial, is unknown. Citric acid can be converted to succinic acid in the TCA cycle on an equimolar basis with the release of 2 moles CO2. However, the level of succinic acid observed here is an order of magnitude greater than what could be produced from citric acid (0.026 moles citric acid per 100 g biomass compared to 0.25 moles succinic acid per 100 g biomass). A number of bacteria, Actinobacillus succinogenes, Mannheimia succiniciproducens, and Aaerobiospirillum succiniproducens, are known to efficiently produce succinic acid (Jansen & Van Gulik, 2014). These strains were not found within the microbiome. Lactic acid bacteria have been shown to produce succinic acid from citric acid (Kaneuchi et al., 1988). Complete conversion of citric acid—added to algal biomass—by lactic acid bacteria could result in succinic acid yields of up to 3.1% of the total biomass weight. Bacteria as the primary source of succinic acid production seems unlikely.

Although algae are not often studied for their ability to derive energy from fermentation, genome sequencing has revealed that among eukaryotes microalgae are the best equipped to undergo anaerobic metabolism in terms of the array of enzymes they possess (Atteia et al., 2013). Pendyala et al. (2020) demonstrated how the anaerobic metabolism of microalgae could be exploited to produce valuable chemical co-products through autofermentation, bypassing preprocessing steps such as sugar hydrolysis for fermentation by another microorganism. They achieved organic acids up to 30% cellular dry weight through mixed acid fermentation by incubating algae biomass in carbonate buffer at pH 10.4. To maintain cellular function in the alkaline environment, microalgae produced a range of extracellular acids from internal carbon stores. Additional reports in the literature suggest succinic acid production by algae is not uncommon. Succinic acid concentrations of up to 7% have been observed in prior algae storage studies (Wendt et al., 2019). A Chlamydomonas mutant that is unable to assemble the hydrogenase active site produced succinic acid when in anoxic environments (Catalanotti et al., 2013). Microarray data and metabolite analysis suggested that carboxylation of pyruvate in this mutant led to the production of malate or oxaloacetate, which was then converted to succinate by the reductive branch of the TCA cycle (Catalanotti et al., 2013). Euglena has been shown to use fumarate as the final electron acceptor, releasing succinic acid in a version of anaerobic respiration (Tielens & Van Hellemond, 1998). Key to this process is the differential expression of succinate dehydrogenase and fumarate reductase. Although both enzymes catalyze the same reaction reversibly in vitro, in vivo they operate in one direction by utilizing different quinones with different reduction potentials (Tielens & Van Hellemond, 1998). Fumarate reductase facilitates the transfer of electrons to fumarate, forming succinic acid and establishing a proton gradient in the process (Tielens et al., 2002). Future work is needed to elucidate the metabolic pathways involved in succinic acid production.

Succinic acid production in storage has the potential to reduce the cost of algae biofuels by recovering succinic acid as a co-product. Wendt et al. (2019) determined that the production of 7% succinic acid (cellular dry weight) could reduce the MFSP of algal biofuels by $0.14 per gallon of gasoline equivalent. The high levels of succinic acid reported here are likely to lead to even greater biofuel cost reductions. Techno-economic analysis (TEA) is needed to understand the cost of treating post-harvest algae biomass with citric acid and the benefit of succinic acid recovery.

Conversion of algae biomass to succinic acid is likely to impact biomass quality. In this study, we assessed how elemental composition changes with storage and saw a slight increase in carbon content when biomass was untreated and no change when treated with citric acid. Elemental composition does not characterize changes to the major biochemical macromolecules of lipid, protein, and carbohydrates. More detailed analysis is needed to understand how changes occurring in post-harvest handling (initial days, post-harvest) and storage (weeks to months, post-harvest) affects downstream processing. Wendt et al. (2019) determined that succinic acid production came at the expense cellular carbohydrate content. The current experiment was not conducted at a sufficient scale to permit carbohydrate analysis of storage replicates. TEA and detailed compositional analysis will help understand the tradeoffs of producing large amounts of succinic acid at the expense of other biomass components.

Conclusions

This study confirms that post-harvest algae biomass is at risk of degradation in the first 24 hr after harvest without intervention. The potential for loss is even greater when biomass is stored for longer periods for seasonal storage. Citric acid amendment could be an effective approach to limit degradation losses in both queuing and long-term storage scenarios, maintaining biomass quality and quantity. Citric acid achieves this benefit through modification of the microbiome. Without citric acid treatment, the algae biomass conditions favor the growth of Clostridia, leading to biomass loss and degradation. Citric acid treatment encourages the growth of lactic acid bacteria, particularly Lactobacillus, and inhibits Clostridia. The stability of post-harvest algae biomass is critical to the economic viability as algae cultivation is costly. We demonstrate here that citric acid treatment goes beyond mere stabilization in support of economic viability by stimulating the accumulation of succinic acid on the order of 29% dry cell weight. The citric acid-induced succinic acid production is simple in nature and requires no additional energy inputs or special operation. The process could be the result of a microalgal metabolic response to extracellular citric acid concentrations. However, due to enrichment of Lactobacillus during storage, bacterial contribution remains a possibility. Collectively, these findings highlight the potential of citric acid treatment as a cost-effective method to improve the economic feasibility of Tetradesmus obliquus UTEX393 for biofuel production.

Supplementary Material

kuag008_Supplemental_Files
kuag008_supplemental_files.zip (9.2KB, zip)

Acknowledgments

The authors would like to thank Kastli Schaller for analytical support.

Contributor Information

Bradley D Wahlen, Bioenergy Feedstock Technologies, Idaho National Laboratory, Idaho Falls, ID, United States.

Chelsea C St Germain, Bioenergy Feedstock Technologies, Idaho National Laboratory, Idaho Falls, ID, United States.

Lynn M Wendt, Bioenergy Feedstock Technologies, Idaho National Laboratory, Idaho Falls, ID, United States.

John McGowen, Arizona Center for Algae Technology and Innovation, Arizona State University, Mesa, AZ, United States.

Yaqi You, Department of Environmental Resources Engineering, SUNY College of Environmental Science and Forestry, Syracuse, NY, United States.

Funding

This work was supported by the U.S. Department of Energy (DOE), the Office of Energy Efficiency and Renewable Energy (EERE), and the Bioenergy Technologies Office (BETO) under award no. DE-AC07-05ID14517. Y.Y. also received support from the Center for Advanced Energy Studies (CAES), a research, education, and innovation consortium consisting of the Idaho National Laboratory and the public research universities of Idaho. The views expressed in this article do not necessarily represent the views of the U.S. Department of Energy or the U.S. government.

Conflicts of interest

None declared.

Data Availabilty

Data will be made available upon request

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