$$\rightleftharpoonup{xx}$$
$$\longleftharp{xx}$$,
$$\longrightharp{xx}$$,
The validation of the phenol-sulfuric-acid method showed good results with a coefficient of determination (r²) of 0.9998 (Table 2). For the 5 g/L concentration the coefficient of variation (CV) and the accuracy showed a good performance with 1.8% and 2.2% error, but lower performance for the 0.25 g/L standard with 5.3% (CV) and 6.1% error (Bias).
The coefficients of determination of both pyruvate-assay calibration curves (with and without matrix) were >0.9999 in a calibration range of 150 µM (Table 3). The coefficients of variation (CV) for the highest and lowest calibration level were <4.6% and the accuracy showed a very good performance over the complete calibration range with less than 3.9% error. Thus, the matrix from the hydrolysis step showed no influence on the enzymatic assay, which is therefore capable to measure pyruvate before and after hydrolysis.
Table 4 shows the detailed results of three exemplary novel strains as successfully identified with the screening platform. The left part of the table displays the results of the automated screening modules concerning viscosity formation, polymer production and the glucose equivalent from the total hydrolysis which were used as evaluation parameters for detailed carbohydrate fingerprint analysis. The carbohydrate fingerprint based on calibrated sugars as well as unknown sugars, dimers and substituents are given in the right part of the table. By use of this information the monomeric composition can be calculated and compared with already known polymer structures. Furthermore, a targeted screening for interesting monomeric compositions and rare carbohydrates can be performed.
The high performance of the micro scale hydrolysis and the HT-PMP-derivatization were demonstrated in our previous work14. Furthermore, the validation of the gel-filtration and the carbohydrate fingerprint for various genera have been described in another publication6. In sum, the screening platform with its modular structure can easily be modified and adapted to individual requirements of the user. The automated screening of the platform enables an eight times higher throughput and gives reliable results. Novel analytical modules like the pyruvate-assay can be integrated and in combination with the carbohydrate fingerprint analysis they provide very detailed information about the identified EPS. Thereby, the screening platform is essential when searching for both slightly modified and completely novel EPS variants.

Figure 1: Overall scheme of the modular high-throughput exopolysaccharide screening platform. The automated screening includes the first three tasks. After bacteria are cultivated in 96-well plates, cells are removed by centrifugation (task 1) and a 96-well filtration (task 2). Then, the remaining monomeric sugars from the growth media are removed via a 96-well gel filtration (task 3). The EPS containing samples are evaluated in task 4. The carbohydrate fingerprint of the screening platform contains the last three tasks. The remaining filtrate of the positive hits from task 2 provides the basis for the gel-filtrate in task 5. After hydrolyzation in task 6 the carbohydrate fingerprint can be analyzed via the HT-PMP method (high-throughput 1-phenyl-3-methyl-5-pyrazolone, task 7). All tasks are followed by different analytical modules and/or a viscosity control. Please click here to view a larger version of this figure.

Figure 2: Robot worktable setup for the screening platform. Layouts of both liquid handling robot worktables are shown: (A) robotic liquid handling system and (B) liquid handling station. (A) The setup consists of a microplate carrier with two positions (positions 1-1 to 1-2), a carrier for disposable tips with four positions (positions 2-1 to 2-4) and three microplate carriers with four positions each (positions 3-1 to 3-4, 4-1 to 4-4 and 5-1 to 5-4). In addition, there is a storage carousel with five hotel carriers (1 to 5) each for seven deep well plates (DWP) and four hotel carriers (6-9) each for 21 micro-titer-plates. The hardware installed on the liquid handling robot is a 96-channel-pipette-arm for use with disposable tips and a robotic manipulator (RM) that moves plates/equipment between the worktable, the storage carousel, the MTP-reader, the centrifuge and the shaking-incubator. (B) The liquid handling station is equipped with a liquid handling arm and an 8-channel 300 µl pipette, a waste container at position 1, a tip adapter with 300 µl tips (position 2), a height adapter 30 with a 250 ml trough (position 3) and five height adapter 60 for MTPs (position 4 to 8). The numbering of the positions is referred to throughout this protocol. Alternative worktables can also be used if there are equivalent setups available. Please click here to view a larger version of this figure.

Figure 3: Pyruvate content of 16 commercially available polymers determined via pyruvate-assay. After the 1 g/L polymer solutions were hydrolyzed and neutralized, the pyruvate-assay was performed from a 1:10 dilution (n = 3). Please click here to view a larger version of this figure.

Figure 4: Flow chart of the modular high-throughput screening platform. The automated screening system, which combines different polysaccharide detection modules: analysis of viscosity formation, polymer production and determination of the total carbohydrate content. The second part provides a detailed monosaccharide analysis for all the selected EPS producers identified in the first part. All data from the automated screening and the data from the carbohydrate fingerprint via UHPLC-ESI-MS are collected in a database and enable the simple identification of structurally related variants of already known EPS or novel EPS and therefore, a targeted screening. Please click here to view a larger version of this figure.
| Main step / Analytical module | Workflow | Observation / Description |
| Cultivation of the strains | 1 ml EPS-mediuma
Pre-culture 48 hr, 30 °C, 1,000 rpma
Main-culture 48 hr, 30 °C, 1,000 rpma | Production of EPS |
| Cell removal / viscosity | Centrifugation: 30 min at 4,300 x g | No pellet = increased viscosity = positive |
| Detection of Polymer: Precipitation | 50 µl supernatant + 150 µl 2-propanolb
Shaking 10 min at RT and 900 rpmb | Visual: Fibers and flakes = positive precipitation of polymer |
| Cell removal / high viscosity | 180 µl supernatant of main-culture
Centrifugation: 10 min at 3,000 x g
1.0 µm glass fiber membrane | No filter passing = high viscosity = positive |
| Detection of Polymer: Precipitation | 50 µl filtrate + 150 µl 2-propanolb
Shaking 10 min at RT and 900 rpmb | Visual: Fibers and flakes = positive precipitation of polymer |
Glucose consumption:
Glucose-assay | Dilution 1:100:
10 µl filtrate + 990 µl ddH2O
50 µl aliquot + 50 µl reagent-mix
Incubation 30 min at 30 °C 150 rpm
Measurement 418-480 nm | Remaining glucose after cultivation |
| Gel-filtration | Equilibration:
3 x 150 µl NH4-acetat buffer pH 5.6
2 x 2 min at 2,000 x g
1 x 2 min at 1,000 x g
Gel-filtration:
35 µl filtrate, 2 min at 1,000 x g
Washing:
3 x 150 µl ddH2O, 2 min at 2,000 x g
75 µl 20% ethanol for storage | Polymer purification:
Removal of salts, pyruvate, glucose and other sugar monomers from cultivation supernatant |
Remaining glucose after gel-filtration
Glucose-assay | Dilution 1:10:
25 µl ddH2O +
20 µl ddH2O and 5 µl filtrate
+ 50 µl reagent-mix
Incubation 30 min at 30 °C, 150 rpm
Measurement 418-480 nm | Subtraction of remaining glucose after gel-filtration from the phenol-sulfuric-acid method |
Glucose equivalent:
Phenol-sulfuric-acid methodc | 20 µl gel-filtrate + 180 µl phenol-sulfuric-acid (30 µl 5% (w/v) phenol in ddH2O + 150 µl conc. H2SO4 (ρ = 1.84 g/ml))
Shaking 5 min at 900 rpm
Incubation 35 min at 80 °C
Measurement at 480 nm | Glucose equivalent:
Δ (phenol-sulfuric-acid value - remaining glucose after gel-filtration)
<300 mg/L negative
>300 and <700 mg/L putative positive
>700 mg/L positive |
| a Handled manually under sterile conditions (laminar flow). |
| b Flammable liquid handled manually under a fume hood. |
| c Phenol-sulfuric-acid handled with Brand Liquid Handling Station (LHS) under a fume hood. |
Table 1: Complete workflow of the automated prescreening with the robotic liquid handling system and the liquid handling station. Overview of all parameters for the automated analytical modules.
| Linearity | LOD | LOQ |
| r²a | Slopea | Offseta | mg/L | mg/L |
| 0.9998 | 0.0007 | -0.021 | 50 | 100 |
|
| Standard | Meanb | Precisionb | Accuracyb |
| mg/L | mg/L | CV% | Bias (%error) |
| 5,000 | 5,112 | 1.8 | 2.2 |
| 250 | 265 | 5.3 | 6.1 |
| a Mean of eight measurements, calibration with six levels glucose from 0.1 to 5 g/L |
| b Performed with a Student’s t-test (α = 0.05; n = 8). |
| LOD: limit of determination, LOQ: limit of quantification, CV: coefficient of variation. |
Table 2: Validation of the phenol-sulfuric-acid method was carried out with the liquid handling station. The linearity was calculated based on a six point calibration (n = 8). Mean, precision and accuracy of two exemplarily chosen glucose concentrations are given here.
| Linearity | LOQ |
| r²a | Slopea | Offseta | µM |
| without matrix | 0.99999 | 0.0223 | -0.0019 | 1 |
| 1:10 diluted matrix | 0.99999 | 0.0221 | -0.0011 | 1 |
|
| Standard | Meanb | Precisionb | Accuracyb |
| µM | µM | CV% | Bias (%error) |
| without matrix | 50 | 49.96 | 3.05 | -0.09 |
| 1 | 1.04 | 2.95 | 3.86 |
| 1:10 diluted matrix | 50 | 49.98 | 0.44 | -0.04 |
| 1 | 1.00 | 4.58 | 0.33 |
| a Mean of three measurements, calibration with six concentrations of pyruvate from 1 to 50 µM. |
| b (n = 3) |
| LOQ: limit of quantification, CV: coefficient of variation. |
Table 3: Validation of the pyruvate-assay with and without a 1:10 diluted neutralized trifluoroacetic-acid-matrix. Two six point calibrations (n = 3) with and without evaluation of matrix influences were performed. Mean, precision and accuracy of two exemplarily chosen pyruvate concentrations with and without effects of a 1:10 dilution were calculated.

Table 4: Results of three exemplary strains screened with the platform. Data collected from the automated screening and the carbohydrate fingerprint. Please click here to download this table as a Microsoft Excel file.
| Carbohydrate | Absorption max [nm] | Absorption at 480 nm mean±SD | Absorbance relative to glucose [%] |
| Diutan gum | 470 | 0.342 | ±0.010 | 187 |
| Gellan gum | 472 | 0.334 | ±0.002 | 183 |
| Guar gum | 478 | 0.387 | ±0.017 | 212 |
| Gummi arabic | 476 | 0.393 | ±0.034 | 215 |
| Hyaluronic acid | 484 | 0.231 | ±0.011 | 126 |
| Karaya gum | 478 | 0.455 | ±0.023 | 249 |
| Konjac gum | 480 | 0.297 | ±0.009 | 163 |
| Larch gum | 480 | 0.337 | ±0.032 | 185 |
| Locust bean gum | 478 | 0.354 | ±0.033 | 194 |
| Scleroglucan | 484 | 0.168 | ±0,010 | 92 |
| Succinoglycan | 482 | 0.168 | ±0.005 | 92 |
| Tara gum | 480 | 0.318 | ±0.016 | 174 |
| Tragacanth | 478 | 0.513 | ±0.003 | 281 |
| Welan gum | 472 | 0.226 | ±0.016 | 124 |
| Xylan | 472 | 0.567 | ±0.007 | 311 |
| Xanthan gum | 482 | 0.245 | ±0.021 | 134 |
| Glucose | 484 | 0.191 | ±0.014 | 100 |
| SD: standard deviation |
Table 5: Results as obtained by the phenol-sulfuric-acid method for 16 commercially available polymers and glucose. The absorption maximum and absorption at 480 nm of 16 commercially available polymers (1 g/L) as well as glucose (1 g/L) were measured applying the phenol-sulfuric-acid method. The absorbance relative to glucose of all the polymers was calculated.
| Standard | Meana | Precisiona | Accuracya |
| mg/L | mg/L | CV% | Bias (%error) |
| 1:10 dilution | 450 | 460 | 1.01 | 2.14 |
| 45 | 44.7 | 1.41 | -0.70 |
| 1:100 dilution | 4,500 | 5,026 | 1.19 | 11.6 |
| 450 | 471 | 1.16 | 4.55 |
| b Performed with a Student’s t-test (α = 0.05; n = 8). |
| CV: coefficient of variation. |
Table 6: Validation of the automated dilution for the glucose-assay. The dilution for the glucose-assay after cultivation (1:100) and after gel-filtration (1:10) were validated. Two glucose concentrations (n = 8) were diluted via the liquid handling system and evaluated. Mean, precision and accuracy were calculated.
| Theoretical glucose value | Covered with silicone cap mat | Test of evaporation (uncovered) | |
| Meana | Precisiona | Accuracya | Meana | Precisiona | Accuracya | Evaporation |
| mg/L | mg/L | CV % | Bias (%error) | mg/L | CV % | Bias (%error) | %error |
| 45.0 | 45.2 | 0.69 | 0.44 | 46.0 | 0.66 | 2.05 | 1.60 |
| 18.0 | 17.7 | 0.80 | -1.68 | 18.0 | 0.72 | -0.01 | 1.69 |
| 9.0 | 8.74 | 1.20 | -2.98 | 8.92 | 0.81 | -0.95 | 2.09 |
| 4.5 | 4.50 | 1.26 | -0.04 | 4.58 | 1.57 | 1.76 | 1.80 |
| 1.8 | 1.85 | 0.74 | 2.90 | 2.01 | 2.82 | 11.6 | 8.48 |
| 0.9 | 1.03 | 1.43 | 14.1 | 1.16 | 3.52 | 28.3 | 12.4 |
| a (n = 4) |
| CV: coefficient of variation. |
Table 7: Evaluation of the evaporation effect of covered and uncovered MTP. Six different glucose standards (n = 4) were stored in the carousel for 3.5 hr at room temperature. The effect of the evaporation was evaluated by using uncovered as well as covered (silicon mat) standard samples. Mean, precision, accuracy and the evaporation in % error were calculated.
| Before gel-filtration | After gel-filtration | Remaining glucose after gel-filtration |
| Meana | SDa | Meana | SDa |
| mg/L | mg/L | mg/L | mg/L | % |
| 1 | 8,647 | 110 | 259 | 121 | 3.00 |
| 2 | 5,108 | 56 | 116 | 37 | 2.27 |
| 3 | 2,014 | 12 | 50.8 | 14 | 2.52 |
| 4 | 1,015 | 12 | 25.1 | 8.1 | 2.47 |
| 5 | 510 | 4.9 | 12.8 | 4.3 | 2.51 |
| 6 | 223 | 8.6 | 6.6 | 1.5 | 2.94 |
| 7 | 122 | 5.6 | 4.3 | 0.9 | 3.48 |
| 8 | 75 | 6.0 | 3.1 | 0.3 | 4.18 |
| a (n=8) |
| SD: standard deviation |
Table 8: Results of the gel-filtration efficiency. Eight different glucose standards were determined before and after gel-filtration to evaluate the efficiency of the gel-filtration. Mean, standard deviation and remaining glucose after gel-filtration in % were calculated.